A novel motion tracking system for evaluation of functional rehabilitation of the upper limbs

Upper limb function impairment is one of the most common sequelae of central nervous system injury, especially in stroke patients and when spinal cord injury produces tetraplegia. Conventional assessment methods cannot provide objective evaluation of patient performance and the tiveness of therapies. The most common assessment tools are based on rating scales, which are inefficient when measuring small changes and can yield subjective bias. In this study, we designed an inertial sensor-based monitoring system composed of five sensors to measure and analyze the complex movements of the upper limbs, which are common in activities of daily living. We developed a kinematic model with nine degrees of freedom to analyze upper limb and head movements in three dimensions. This system was then validated using a commercial optoelectronic system. These findings suggest that an inertial sensor-based motion tracking system can be used in patients who have upper limb impairment through data integration with a virtual reality-based neuroretation system.

Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

Non-invasive user monitoring in daily tasks for cognitive rehabilitation

El uso de técnicas para la monitorización del movimiento humano generalmente permite a los investigadores analizar la cinemática y especialmente las capacidades motoras en aquellas actividades de la vida cotidiana que persiguen un objetivo concreto como pueden ser la preparación de bebidas y comida, e incluso en tareas de aseo. Adicionalmente, la evaluación del movimiento y el comportamiento humanos en el campo de la rehabilitación cognitiva es esencial para profundizar en las dificultades que algunas personas encuentran en la ejecución de actividades diarias después de accidentes cerebro-vasculares. Estas dificultades están principalmente asociadas a la realización de pasos secuenciales y al reconocimiento del uso de herramientas y objetos. La interpretación de los datos sobre la actitud de este tipo de pacientes para reconocer y determinar el nivel de éxito en la ejecución de las acciones, y para ampliar el conocimiento en las enfermedades cerebrales, sus consecuencias y severidad, depende totalmente de los dispositivos usados para la captura de esos datos y de la calidad de los mismos. Más aún, existe una necesidad real de mejorar las técnicas actuales de rehabilitación cognitiva contribuyendo al diseño de sistemas automáticos para crear una especie de terapeuta virtual que asegure una vida más independiente de estos pacientes y reduzca la carga de trabajo de los terapeutas. Con este objetivo, el uso de sensores y dispositivos para obtener datos en tiempo real de la ejecución y estado de la tarea de rehabilitación es esencial para también contribuir al diseño y entrenamiento de futuros algoritmos que pudieran reconocer errores automáticamente para informar al paciente acerca de ellos mediante distintos tipos de pistas como pueden ser imágenes, mensajes auditivos o incluso videos. La tecnología y soluciones existentes en este campo no ofrecen una manera totalmente robusta y efectiva para obtener datos en tiempo real, por un lado, porque pueden influir en el movimiento del propio paciente en caso de las plataformas basadas en el uso de marcadores que necesitan sensores pegados en la piel; y por otro lado, debido a la complejidad o alto coste de implantación lo que hace difícil pensar en la idea de instalar un sistema en el hospital o incluso en la casa del paciente. Esta tesis presenta la investigación realizada en el campo de la monitorización del movimiento de pacientes para proporcionar un paso adelante en términos de detección, seguimiento y reconocimiento del comportamiento de manos, gestos y cara mediante una manera no invasiva la cual puede mejorar la técnicas actuales de rehabilitación cognitiva para la adquisición en tiempo real de datos sobre el comportamiento del paciente y la ejecución de la tarea. Para entender la importancia del marco de esta tesis, inicialmente se presenta un resumen de las principales enfermedades cognitivas y se introducen las consecuencias que tienen en la ejecución de tareas de la vida diaria. Más aún, se investiga sobre las metodologías actuales de rehabilitación cognitiva. Teniendo en cuenta que las manos son la principal parte del cuerpo para la ejecución de tareas manuales de la vida cotidiana, también se resumen las tecnologías existentes para la captura de movimiento de manos. Una de las principales contribuciones de esta tesis está relacionada con el diseño y evaluación de una solución no invasiva para detectar y seguir las manos durante la ejecución de tareas manuales de la vida cotidiana que a su vez involucran la manipulación de objetos. Esta solución la cual no necesita marcadores adicionales y está basada en una cámara de profundidad de bajo coste, es robusta, precisa y fácil de instalar. Otra contribución presentada se centra en el reconocimiento de gestos para detectar el agarre de objetos basado en un sensor infrarrojo de última generación, y también complementado con una cámara de profundidad. Esta nueva técnica, y también no invasiva, sincroniza ambos sensores para seguir objetos específicos además de reconocer eventos concretos relacionados con tareas de aseo. Más aún, se realiza una evaluación preliminar del reconocimiento de expresiones faciales para analizar si es adecuado para el reconocimiento del estado de ánimo durante la tarea. Por su parte, todos los componentes y algoritmos desarrollados son integrados en un prototipo simple para ser usado como plataforma de monitorización. Se realiza una evaluación técnica del funcionamiento de cada dispositivo para analizar si es adecuada para adquirir datos en tiempo real durante la ejecución de tareas cotidianas reales. Finalmente, se estudia la interacción con pacientes reales para obtener información del nivel de usabilidad del prototipo. Dicha información es esencial y útil para considerar una rehabilitación cognitiva basada en la idea de instalación del sistema en la propia casa del paciente al igual que en el hospital correspondiente. ABSTRACT The use of human motion monitoring techniques usually let researchers to analyse kinematics, especially in motor strategies for goal-oriented activities of daily living, such as the preparation of drinks and food, and even grooming tasks. Additionally, the evaluation of human movements and behaviour in the field of cognitive rehabilitation is essential to deep into the difficulties some people find in common activities after stroke. This difficulties are mainly associated with sequence actions and the recognition of tools usage. The interpretation of attitude data of this kind of patients in order to recognize and determine the level of success of the execution of actions, and to broaden the knowledge in brain diseases, consequences and severity, depends totally on the devices used for the capture of that data and the quality of it. Moreover, there is a real need of improving the current cognitive rehabilitation techniques by contributing to the design of automatic systems to create a kind of virtual therapist for the improvement of the independent life of these stroke patients and to reduce the workload of the occupational therapists currently in charge of them. For this purpose, the use of sensors and devices to obtain real time data of the execution and state of the rehabilitation task is essential to also contribute to the design and training of future smart algorithms which may recognise errors to automatically provide multimodal feedback through different types of cues such as still images, auditory messages or even videos. The technology and solutions currently adopted in the field don't offer a totally robust and effective way for obtaining real time data, on the one hand, because they may influence the patient's movement in case of marker-based platforms which need sensors attached to the skin; and on the other hand, because of the complexity or high cost of implementation, which make difficult the idea of installing a system at the hospital or even patient's home. This thesis presents the research done in the field of user monitoring to provide a step forward in terms of detection, tracking and recognition of hand movements, gestures and face via a non-invasive way which could improve current techniques for cognitive rehabilitation for real time data acquisition of patient's behaviour and execution of the task. In order to understand the importance of the scope of the thesis, initially, a summary of the main cognitive diseases that require for rehabilitation and an introduction of the consequences on the execution of daily tasks are presented. Moreover, research is done about the actual methodology to provide cognitive rehabilitation. Considering that the main body members involved in the completion of a handmade daily task are the hands, the current technologies for human hands movements capture are also highlighted. One of the main contributions of this thesis is related to the design and evaluation of a non-invasive approach to detect and track user's hands during the execution of handmade activities of daily living which involve the manipulation of objects. This approach does not need the inclusion of any additional markers. In addition, it is only based on a low-cost depth camera, it is robust, accurate and easy to install. Another contribution presented is focused on the hand gesture recognition for detecting object grasping based on a brand new infrared sensor, and also complemented with a depth camera. This new, and also non-invasive, solution which synchronizes both sensors to track specific tools as well as recognize specific events related to grooming is evaluated. Moreover, a preliminary assessment of the recognition of facial expressions is carried out to analyse if it is adequate for recognizing mood during the execution of task. Meanwhile, all the corresponding hardware and software developed are integrated in a simple prototype with the purpose of being used as a platform for monitoring the execution of the rehabilitation task. Technical evaluation of the performance of each device is carried out in order to analyze its suitability to acquire real time data during the execution of real daily tasks. Finally, a kind of healthcare evaluation is also presented to obtain feedback about the usability of the system proposed paying special attention to the interaction with real users and stroke patients. This feedback is quite useful to consider the idea of a home-based cognitive rehabilitation as well as a possible hospital installation of the prototype.

Estudio cinemático del cuerpo humano mediante Kinect

La cámara Kinect está desarrollada por Prime Sense en colaboración con Microsoft para la consola XBox, ofrece imágenes de profundidad gracias a un sensor infrarrojo. Este dispositivo también incluye una cámara RGB que ofrece imágenes a color además de una serie de micrófonos colocados de tal manera que son capaces de saber de qué ángulo proviene el sonido. En un principio Kinect se creó para el ocio doméstico pero su bajo precio (en comparación con otras cámaras de iguales características) y la aceptación por parte de desarrolladores han explotado sus posibilidades. El objetivo de este proyecto es, partiendo de estos datos, la obtención de variables cinemáticas tales como posición, velocidad y aceleración de determinados puntos de control del cuerpo de un individuo como pueden ser el cabeza, cuello, hombros, codos, muñecas, caderas, rodillas y tobillos a partir de los cuales poder extraer patrones de movimiento. Para ello se necesita un middleware mediante el entorno de libre distribución (GNU) multiplataforma. Como IDE se ha utilizado Processing, un entorno open source creado para proyectos de diseño. Además se ha utilizado el contenedor SimpleOpenNI, desarrollado por estudiantes e investigadores que trabajan con Kinect. Esto ofrece la posibilidad de prescindir del SDK de Microsoft, el cual es propietario y obliga a utilizar su sistema operativo, Windows. Usando estas herramientas se consigue una solución viable para varios sistemas operativos. Se han utilizado métodos y facilidades que ofrece el lenguaje orientado a objetos Java (Proccesing hereda de este), y se ha planteado una solución basada en un modelo cliente servidor que dota de escalabilidad al proyecto. El resultado del proyecto es útil en aplicaciones para poblaciones con riesgo de exclusión (como es el espectro autista), en telediagnóstico, y en general entornos donde se necesite estudiar hábitos y comportamientos a partir del movimiento humano. Con este proyecto se busca tener una continuidad mediante otras aplicaciones que analicen los datos ofrecidos. ABSTRACT. The Kinect camera is developed by PrimeSense in collaboration with Microsoft for the xBox console provides depth images thanks to an infrared sensor. This device also includes an RGB camera that provides color images in addition to a number of microphones placed such that they are able to know what angle the sound comes. Kinect initially created for domestic leisure but its low prices (compared to other cameras with the same characteristics) and acceptance by developers have exploited its possibilities. The objective of this project is based on this data to obtain kinematic variables such as position, velocity and acceleration of certain control points of the body of an individual from which to extract movement patterns. These points can be the head, neck, shoulders, elbows, wrists, hips, knees and ankles. This requires a middleware using freely distributed environment (GNU) platform. Processing has been used as a development environment, and open source environment created for design projects. Besides the container SimpleOpenNi has been used, it developed by students and researchers working with Kinect. This offers the possibility to dispense with the Microsoft SDK which owns and agrees to use its operating system, Windows. Using these tools will get a viable solution for multiple operating systems. We used methods and facilities of the Java object-oriented language (Processing inherits from this) and has proposed a solution based on a client-server model which provides scalability to the project. The result of the project is useful in applications to populations at risk of exclusion (such as autistic spectrum), in remote diagnostic, and in general environments that need study habits and behaviors from human motion. This project aims to have continuity using other applications to analyze the data provided.

Paisaje de energías: conocimiento estético en el enfoque ambiental del proyecto

Desde hace ya varias décadas la praxis de la ecología ha venido reconociendo la necesidad de estudiar los múltiples sistemas de interacción del ser humano, como especie viva, y su entorno. Entidades espaciales como el paisaje geográfico son empleadas para delimitar sistemas territoriales operados por la sociedad, precisando campos concretos de su acción física, biológica y cultural. La ecología aborda así el conocimiento científico del territorio como asentamiento humano, rastrea sus patrones espaciales y analiza su compleja estructura funcional. En ese contexto, la transferencia de herramientas e instrumentos desde la ecología al ámbito proyectivo posee ya un bagaje de más de cinco décadas. Cada vez con más frecuencia el proyecto emplea parámetros, inventarios, fórmulas, indicadores y tecnologías que tratan de dar una respuesta ambientalmente adecuada a los condicionantes de contorno, por ejemplo aprovechando las condiciones climáticas en la optimización energética o proponiendo programas de usos del suelo que eviten perturbaciones en ecosistemas de interés. Con todo, en el momento presente surgen voces que, ante el dominio indiscutible de los enfoques netamente deterministas, tratan de recordar que los principios del pensamiento ecológico van más allá del mero control cuantitativo de los procesos biofísicos. Recuerdan que la etología demostró a principios del XX que el ser humano, como ser consciente, inviste una relación de intimidad con su entorno que supera tales perspectivas: a través de la correspondencia entre percepción y significación, entre lo físico y lo psíquico, entre interioridad y exterioridad, las personas abrazan la plenitud de aquello que les rodea en un acto de profunda conciliación afectiva. De tal ligadura de intimidad depende, sí o sí, y en toda su profundidad, la aceptación humana del entorno construido. A través de la noción de ambiente [Umwelt] se demuestra que la relación del hombre con su entorno es inseparable, bidireccional y coordinada y, por lo tanto, desde una posición coherente, la experiencia del espacio puede ser examinada a partir de la reciprocidad que constituyen, en continuidad, la persona y el lugar. De esta forma, la tesis dirige su objetivo principal a explorar y considerar, desde el proyecto, el significado y la influencia de la experiencia ambiental del espacio construido en la vida humana. Es más que probable que buena parte de los problemas de desafección del hombre con los paisajes transformados de su contemporaneidad tenga que ver con que tanto las intensidades de la experiencia y percepción humana, como la potestad interpretativa de sus productos culturales, incluyendo la arquitectura, han sido fuertemente reducidas. Ante este problema, la investigación toma como hipótesis la oportunidad que ofrece el pensamiento ecológico de reformular la experiencia estética como un acto de conocimiento, como un evento donde se da el encuentro físico y se construyen significados, donde se sancionan valores sociales y se mira hacia el futuro. Se ha de señalar que la presente tesis doctoral arranca en el Laboratorio de Paisaje del Grupo de Investigación Paisaje Cultural de la Universidad Politécnica de Madrid dirigido por Concha Lapayese y Darío Gazapo, y por tanto hace suyos para el estado del arte los principales conceptos e ideas bajo los que el trabajo teórico y práctico del grupo se viene orientando desde hace años: la consideración del paisaje como acontecimiento; la oscilación de la interpretación entre un paisaje específico y un paisaje genérico en un mundo globalizado; el reconocimiento de la experiencia estética del paisaje como una toma de conciencia social; y en definitiva, la reivindicación de la interioridad en el proyecto contemporáneo. La investigación profundiza en una línea de oportunidad que se abre al promover lo que se ha llamado un conocimiento por lo sentido como estrategia ambiental que permite contrarrestar mitos profundamente arraigados en las estructuras sociales. El primer paso en ese recorrido sería explorar ecológicamente el aporte de la experiencia estética; esto es, su consideración como forma de conocimiento específico. Resultaría pertinente impulsar la idea de la inmersión en el paisaje como fenómeno experiencial, sensual y corporal, y enfrentar, desde ahí, el problema de la aceptación social de lo nuevo y lo trasformado de acuerdo con el momento actual. La exploración sobre la afectividad en el ambiente no es, en cualquier caso, un asunto nuevo. Sin pretensiones de historiografía, dos momentos del siglo XX concentran el interés de la investigación. La primera se corresponde fundamentalmente con la segunda década del siglo, en relación a una serie de influencias que desde los avances científicos determinaron singulares aventuras del arte más experimental. La segunda se posiciona en el entorno de 1970, época en la que es conocido el interés que despertaron las cuestiones ambientales. En ambos casos se han estudiado aportaciones que desvelan conceptos determinantes en la definición de la experiencia estética como un evento de adquisición de conocimiento por lo sentido. Es conveniente adelantar el rol de centralidad que para la investigación tiene el concepto de energía, tal como el propio título subraya. La energía como realidad material y sensible es el sustrato que permite navegar por el principio de unidad epistemológica que subyace al pensamiento ecológico. Sus continuas referencias simbólicas, físicas y metafóricas entre los artistas estudiados no son un mero recurso iconográfico: mantienen inherente el principio de continuidad ambiental en el cual el ser humano y la inmensidad del cosmos navegan indisociables. Un discurso unificado y consistente sobre los aportes de la experiencia estética enfocada como forma de conocimiento por lo sentido hila la lectura histórica, conceptual y práctica de toda la investigación. Con ello se alcanza a hilvanar un diagrama conceptual, modelo de análisis proyectivo, que recoge ideas científicas, filosóficas y proyectivas. De alguna manera, el diagrama trata de dibujar, desde los principios del pensamiento ecológico, la correlación de continuidad que, vacilante, tensa, sutil y frágil se desplaza incesante e irresuelta entre interioridad y exterioridad. ABSTRACT Over the last few decades ecological practice has come to acknowledge a need for studying the multiple systems of interaction between the human being - inasmuch as it is a living species - and its environment. Spatial entities such as the geographic notion of landscape have been used to delimitate the territorial systems operated by society and to describe in detail specific fields of its physical, biological and cultural action. Ecology has thus managed to address the scientific knowledge of the territory as a human settlement, tracking its spatial patterns and analysing its complex functional structure. In this context, the transfer of tools and instruments from the field of ecology to that of design has a tradition already going back more than fifty years. Increasingly more often, design makes use of parameters, inventories, formulas, indicators and technologies to give an environmentally sound response to contour conditions: for instance, taking advantage of the local climate for the optimisation of energy consumption or proposing land uses that avoid disturbing valuable ecosystems. Yet in the present day some voices have arisen that, against the uncontested domination of purely positivistic approaches, are trying to draw attention to the fact that the principles of ecological thought go beyond mere quantitative control of biophysical processes. They point out that, in the early 20th century, ethology proved that the human being, as a conscious entity, invests itself into a relationship of intimacy with its environment that surpasses such perspectives: through the correspondences between perception and signification, between physical and psychological or between inside and outside, people embrace the entirety of their surroundings in an action of deep affective conciliation. It is on this link of intimacy that - fully and unquestionably - human acceptance of the built environment depends. Through the notion of environment [Umwelt] it can be proven that the relationship between the human being and its environment is inseparable, bidirectional and coordinated; and that, therefore, from a coherent position the experience of space can be examined through the reciprocity constituted continuously by person and place. Thus, the main goal in this thesis is to explore and acknowledge, from the standpoint of design, the meaning and influence of the environmental experience in human life. It is extremely likely that many of the issues with mankind’s alienation from the transformed landscapes of the present day arise from the fact that both the intensity of human perception and experience and the interpretive capacity of its cultural products –including architecture - have been greatly reduced. Facing this issue, research has taken as hypothesis the opportunity offered by ecological thought of reformulating aesthetic experience as an act of knowledge – as an event where physical encounter takes place and meanings are constructed; where social values are sanctioned and the path towards the future is drawn. This notwithstanding, the present thesis began in the Landscape Laboratory of the Technical University of Madrid Cultural Landscape Research Group (GIPC-UPM), led by Concha Lapayese and Darío Gazapo; and has therefore appropriated for its state of the art the main concepts and ideas that have been orienting the practical and theoretical work of the latter: the understanding of landscape as an event, the oscillation of interpretation between a specific and a generic landscape within a globalised world; the acknowledgement of the aesthetic experience of landscape as a way of acquiring social awareness; and, all in all, a vindication of interiority in contemporary design. An exploration has been made of the line of opportunity that is opened when promoting what has been termed knowledge through the senses as an environmental strategy allowing to counter myths deeply rooted in social structures. The first step in this path would be an ecological exploration of the contribution of the aesthetic experience; that is, its consideration as a type of specific knowledge. It would be pertinent to further the idea of immersion into the landscape as an experiential, sensual and corporeal phenomenon and, from that point, to face the issue of social acceptance of what is new and transformed according to the values of the present day. The exploration of affectivity in the environment is not, at any rate, a new topic. Without aspiring to make a history of it, we can mark two points in the 20th century that have concentrated the interest of this research. The first coincides with the second decade of the century and relates to a number of influences that, arising from scientific progress, determined the singular adventures of the more experimental tendencies in art. The second is centred around 1970: a period in which the interest drawn by environmental matters is well known. In both cases, contributions have been studied that reveal crucial concepts in defining the aesthetic experience as an event for the acquisition of knowledge through the senses. It is necessary to highlight the role of centrality that the concept of energy has throughout this research, as is evident even in its title. Energy as a material, sensitive reality is the substrate making it possible to navigate through the principle of epistemological unity underlying ecological thought. The continuous symbolic, physical and metaphorical references to it among the artists studied here are not a mere iconographic source: they remind of the inherency of the principle of environmental continuity within which the human being and the immensity of cosmos travel indissociably. A unified, consistent discourse on the contributions of the aesthetic experience addressed as knowledge through the senses weaves together the historic, conceptual and practical reading of the whole research. With it, a conceptual diagram is constructed – a model of design analysis – gathering together scientific, philosophical and design ideas. Somehow, the diagram tries to draw from the principles of ecological thought the correlation of continuity that, vacillating, tense, subtle and fragile, shifts incessantly and unresolved between interiority and exteriority.

In-loop Feature Tracking for Structure and Motion with Out-of-core Optimization

In this paper, a novel and approach for obtaining 3D models from video sequences captured with hand-held cameras is addressed. We define a pipeline that robustly deals with different types of sequences and acquiring devices. Our system follows a divide and conquer approach: after a frame decimation that pre-conditions the input sequence, the video is split into short-length clips. This allows to parallelize the reconstruction step which translates into a reduction in the amount of computational resources required. The short length of the clips allows an intensive search for the best solution at each step of reconstruction which robustifies the system. The process of feature tracking is embedded within the reconstruction loop for each clip as opposed to other approaches. A final registration step, merges all the processed clips to the same coordinate frame

Study and analysis of the Leap Motion sensor and the Software Development Kit (SDK) for the implementation of visual Human Computer Interfaces

En este proyecto, se presenta un informe técnico sobre la cámara Leap Motion y el Software Development Kit correspondiente, el cual es un dispositivo con una cámara de profundidad orientada a interfaces hombre-máquina. Esto es realizado con el propósito de desarrollar una interfaz hombre-máquina basada en un sistema de reconocimiento de gestos de manos. Después de un exhaustivo estudio de la cámara Leap Motion, se han realizado diversos programas de ejemplo con la intención de verificar las capacidades descritas en el informe técnico, poniendo a prueba la Application Programming Interface y evaluando la precisión de las diferentes medidas obtenidas sobre los datos de la cámara. Finalmente, se desarrolla un prototipo de un sistema de reconocimiento de gestos. Los datos sobre la posición y orientación de la punta de los dedos obtenidos de la Leap Motion son usados para describir un gesto mediante un vector descriptor, el cual es enviado a una Máquina Vectores Soporte, utilizada como clasificador multi-clase.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Efficient Model-based 3D Tracking by Using Direct Image Registration

This thesis deals with the problem of efficiently tracking 3D objects in sequences of images. We tackle the efficient 3D tracking problem by using direct image registration. This problem is posed as an iterative optimization procedure that minimizes a brightness error norm. We review the most popular iterative methods for image registration in the literature, turning our attention to those algorithms that use efficient optimization techniques. Two forms of efficient registration algorithms are investigated. The first type comprises the additive registration algorithms: these algorithms incrementally compute the motion parameters by linearly approximating the brightness error function. We centre our attention on Hager and Belhumeur’s factorization-based algorithm for image registration. We propose a fundamental requirement that factorization-based algorithms must satisfy to guarantee good convergence, and introduce a systematic procedure that automatically computes the factorization. Finally, we also bring out two warp functions to register rigid and nonrigid 3D targets that satisfy the requirement. The second type comprises the compositional registration algorithms, where the brightness function error is written by using function composition. We study the current approaches to compositional image alignment, and we emphasize the importance of the Inverse Compositional method, which is known to be the most efficient image registration algorithm. We introduce a new algorithm, the Efficient Forward Compositional image registration: this algorithm avoids the necessity of inverting the warping function, and provides a new interpretation of the working mechanisms of the inverse compositional alignment. By using this information, we propose two fundamental requirements that guarantee the convergence of compositional image registration methods. Finally, we support our claims by using extensive experimental testing with synthetic and real-world data. We propose a distinction between image registration and tracking when using efficient algorithms. We show that, depending whether the fundamental requirements are hold, some efficient algorithms are eligible for image registration but not for tracking.

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

Approximate Analytical Model for the Squeeze-Film Lubrication of the Human Ankle Joint with Synovial Fluid Filtrated by Articular Cartilage

The aim of this article is to propose an analytical approximate squeeze-film lubrication model of the human ankle joint for a quick assessment of the synovial pressure field and the load carrying due to the squeeze motion. The model starts from the theory of boosted lubrication for the human articular joints lubrication (Walker et al., Rheum Dis 27:512–520, 1968; Maroudas, Lubrication and wear in joints. Sector, London, 1969) and takes into account the fluid transport across the articular cartilage using Darcy’s equation to depict the synovial fluid motion through a porous cartilage matrix. The human ankle joint is assumed to be cylindrical enabling motion in the sagittal plane only. The proposed model is based on a modified Reynolds equation; its integration allows to obtain a quick assessment on the synovial pressure field showing a good agreement with those obtained numerically (Hlavacek, J Biomech 33:1415–1422, 2000). The analytical integration allows the closed form description of the synovial fluid film force and the calculation of the unsteady gap thickness.

Communication Architecture for Tracking and Interoperable Services at Hospitals: A Real Deployment Experience

Any new hospital communication architecture has to support existing services, but at the same time new added features should not affect normal tasks. This article deals with issues regarding old and new systems’ interoperability, as well as the effect the human factor has in a deployed architecture. It also presents valuable information, which is a product of a real scenario. Tracking services are also tested in order to monitor and administer several medical resources.

Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion

Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

IDT-3D: Identification and tracking in controlled environments using a 3D unified user interface

Identification and tracking of objects in specific environments such as harbors or security areas is a matter of great importance nowadays. With this purpose, numerous systems based on different technologies have been developed, resulting in a great amount of gathered data displayed through a variety of interfaces. Such amount of information has to be evaluated by human operators in order to take the correct decisions, sometimes under highly critical situations demanding both speed and accuracy. In order to face this problem we describe IDT-3D, a platform for identification and tracking of vessels in a harbour environment able to represent fused information in real time using a Virtual Reality application. The effectiveness of using IDT-3D as an integrated surveillance system is currently under evaluation. Preliminary results point to a significant decrease in the times of reaction and decision making of operators facing up a critical situation. Although the current application focus of IDT-3D is quite specific, the results of this research could be extended to the identification and tracking of targets in other controlled environments of interest as coastlines, borders or even urban areas.