IFTrace: Video segmentation of deformable objects using the Image Foresting Transform

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

CART application to image primitives tracking

[EN] [EN] In this paper we present a new method for image primitives tracking based on a CART (Classification and Regression Tree). Primitives tracking procedure uses lines and circles as primitives. We have applied the proposed method to sport event scenarios, specifically, soccer matches. We estimate CART parameters using a learning procedure based on RGB image channels. In order to illustrate its performance, it has been applied to real HD (High Definition) video sequences and some numerical experiments are shown. The quality of the primitives tracking with the decision tree is validated by the percentage error rates obtained and the comparison with other techniques as a morphological method. We also present applications of the proposed method to camera calibration and graphic object insertion in real video sequences.

On-line adaptive visual tracking

Visual tracking is the problem of estimating some variables related to a target given a video sequence depicting the target. Visual tracking is key to the automation of many tasks, such as visual surveillance, robot or vehicle autonomous navigation, automatic video indexing in multimedia databases. Despite many years of research, long term tracking in real world scenarios for generic targets is still unaccomplished. The main contribution of this thesis is the definition of effective algorithms that can foster a general solution to visual tracking by letting the tracker adapt to mutating working conditions. In particular, we propose to adapt two crucial components of visual trackers: the transition model and the appearance model. The less general but widespread case of tracking from a static camera is also considered and a novel change detection algorithm robust to sudden illumination changes is proposed. Based on this, a principled adaptive framework to model the interaction between Bayesian change detection and recursive Bayesian trackers is introduced. Finally, the problem of automatic tracker initialization is considered. In particular, a novel solution for categorization of 3D data is presented. The novel category recognition algorithm is based on a novel 3D descriptors that is shown to achieve state of the art performances in several applications of surface matching.

Riabilitazione e valutazione di pazienti con deficit neurologici mediante l'utilizzo di realtà virtuale, feedback aumentati, sensori inerziali e tecnologie video a basso costo.

La neuroriabilitazione è un processo attraverso cui individui affetti da patologie neurologiche mirano al conseguimento di un recupero completo o alla realizzazione del loro potenziale ottimale benessere fisico, mentale e sociale. Elementi essenziali per una riabilitazione efficace sono: una valutazione clinica da parte di un team multidisciplinare, un programma riabilitativo mirato e la valutazione dei risultati conseguiti mediante misure scientifiche e clinicamente appropriate. Obiettivo principale di questa tesi è stato sviluppare metodi e strumenti quantitativi per il trattamento e la valutazione motoria di pazienti neurologici. I trattamenti riabilitativi convenzionali richiedono a pazienti neurologici l’esecuzione di esercizi ripetitivi, diminuendo la loro motivazione. La realtà virtuale e i feedback sono in grado di coinvolgerli nel trattamento, permettendo ripetibilità e standardizzazione dei protocolli. È stato sviluppato e valutato uno strumento basato su feedback aumentati per il controllo del tronco. Inoltre, la realtà virtuale permette l’individualizzare il trattamento in base alle esigenze del paziente. Un’applicazione virtuale per la riabilitazione del cammino è stata sviluppata e testata durante un training su pazienti di sclerosi multipla, valutandone fattibilità e accettazione e dimostrando l'efficacia del trattamento. La valutazione quantitativa delle capacità motorie dei pazienti viene effettuata utilizzando sistemi di motion capture. Essendo il loro uso nella pratica clinica limitato, una metodologia per valutare l’oscillazione delle braccia in soggetti parkinsoniani basata su sensori inerziali è stata proposta. Questi sono piccoli, accurati e flessibili ma accumulano errori durante lunghe misurazioni. È stato affrontato questo problema e i risultati suggeriscono che, se il sensore è sul piede e le accelerazioni sono integrate iniziando dalla fase di mid stance, l’errore e le sue conseguenze nella determinazione dei parametri spaziali sono contenuti. Infine, è stata presentata una validazione del Kinect per il tracking del cammino in ambiente virtuale. Risultati preliminari consentono di definire il campo di utilizzo del sensore in riabilitazione.

Seeing Spaces: An Eye-Tracking Study Of Speech Segmentation

Speech is often a multimodal process, presented audiovisually through a talking face. One area of speech perception influenced by visual speech is speech segmentation, or the process of breaking a stream of speech into individual words. Mitchel and Weiss (2013) demonstrated that a talking face contains specific cues to word boundaries and that subjects can correctly segment a speech stream when given a silent video of a speaker. The current study expanded upon these results, using an eye tracker to identify highly attended facial features of the audiovisual display used in Mitchel and Weiss (2013). In Experiment 1, subjects were found to spend the most time watching the eyes and mouth, with a trend suggesting that the mouth was viewed more than the eyes. Although subjects displayed significant learning of word boundaries, performance was not correlated with gaze duration on any individual feature, nor was performance correlated with a behavioral measure of autistic-like traits. However, trends suggested that as autistic-like traits increased, gaze duration of the mouth increased and gaze duration of the eyes decreased, similar to significant trends seen in autistic populations (Boratston & Blakemore, 2007). In Experiment 2, the same video was modified so that a black bar covered the eyes or mouth. Both videos elicited learning of word boundaries that was equivalent to that seen in the first experiment. Again, no correlations were found between segmentation performance and SRS scores in either condition. These results, taken with those in Experiment, suggest that neither the eyes nor mouth are critical to speech segmentation and that perhaps more global head movements indicate word boundaries (see Graf, Cosatto, Strom, & Huang, 2002). Future work will elucidate the contribution of individual features relative to global head movements, as well as extend these results to additional types of speech tasks.

Real-time Human Motion Capture with Simple Marker Sets and Monocular Video

In this paper we present a hybrid method to track human motions in real-time. With simplified marker sets and monocular video input, the strength of both marker-based and marker-free motion capturing are utilized: A cumbersome marker calibration is avoided while the robustness of the marker-free tracking is enhanced by referencing the tracked marker positions. An improved inverse kinematics solver is employed for real-time pose estimation. A computer-visionbased approach is applied to refine the pose estimation and reduce the ambiguity of the inverse kinematics solutions. We use this hybrid method to capture typical table tennis upper body movements in a real-time virtual reality application.

Visual Fixation for 3D Video Stabilization

Visual fixation is employed by humans and some animals to keep a specific 3D location at the center of the visual gaze. Inspired by this phenomenon in nature, this paper explores the idea to transfer this mechanism to the context of video stabilization for a handheld video camera. A novel approach is presented that stabilizes a video by fixating on automatically extracted 3D target points. This approach is different from existing automatic solutions that stabilize the video by smoothing. To determine the 3D target points, the recorded scene is analyzed with a stateof- the-art structure-from-motion algorithm, which estimates camera motion and reconstructs a 3D point cloud of the static scene objects. Special algorithms are presented that search either virtual or real 3D target points, which back-project close to the center of the image for as long a period of time as possible. The stabilization algorithm then transforms the original images of the sequence so that these 3D target points are kept exactly in the center of the image, which, in case of real 3D target points, produces a perfectly stable result at the image center. Furthermore, different methods of additional user interaction are investigated. It is shown that the stabilization process can easily be controlled and that it can be combined with state-of-theart tracking techniques in order to obtain a powerful image stabilization tool. The approach is evaluated on a variety of videos taken with a hand-held camera in natural scenes.

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

How can video analysis help laparoscopic surgeons?

Automatic analysis of minimally invasive surgical (MIS) video has the potential to drive new solutions that alleviate existing needs for safer surgeries: reproducible training programs, objective and transparent assessment systems and navigation tools to assist surgeons and improve patient safety. As an unobtrusive, always available source of information in the operating room (OR), this research proposes the use of surgical video for extracting useful information during surgical operations. Methodology proposed includes tools' tracking algorithm and 3D reconstruction of the surgical field. The motivation for these solutions is the augmentation of the laparoscopic view in order to provide orientation aids, optimal surgical path visualization, or preoperative virtual models overlay

Applications for wireless sensor networks : tracking with binary proximity sensors

El interés cada vez mayor por las redes de sensores inalámbricos pueden ser entendido simplemente pensando en lo que esencialmente son: un gran número de pequeños nodos sensores autoalimentados que recogen información o detectan eventos especiales y se comunican de manera inalámbrica, con el objetivo final de entregar sus datos procesados a una estación base. Los nodos sensores están densamente desplegados dentro del área de interés, se pueden desplegar al azar y tienen capacidad de cooperación. Por lo general, estos dispositivos son pequeños y de bajo costo, de modo que pueden ser producidos y desplegados en gran numero aunque sus recursos en términos de energía, memoria, velocidad de cálculo y ancho de banda están enormemente limitados. Detección, tratamiento y comunicación son tres elementos clave cuya combinación en un pequeño dispositivo permite lograr un gran número de aplicaciones. Las redes de sensores proporcionan oportunidades sin fin, pero al mismo tiempo plantean retos formidables, tales como lograr el máximo rendimiento de una energía que es escasa y por lo general un recurso no renovable. Sin embargo, los recientes avances en la integración a gran escala, integrado de hardware de computación, comunicaciones, y en general, la convergencia de la informática y las comunicaciones, están haciendo de esta tecnología emergente una realidad. Del mismo modo, los avances en la nanotecnología están empezando a hacer que todo gire entorno a las redes de pequeños sensores y actuadores distribuidos. Hay diferentes tipos de sensores tales como sensores de presión, acelerómetros, cámaras, sensores térmicos o un simple micrófono. Supervisan las condiciones presentes en diferentes lugares tales como la temperatura, humedad, el movimiento, la luminosidad, presión, composición del suelo, los niveles de ruido, la presencia o ausencia de ciertos tipos de objetos, los niveles de tensión mecánica sobre objetos adheridos y las características momentáneas tales como la velocidad , la dirección y el tamaño de un objeto, etc. Se comprobara el estado de las Redes Inalámbricas de Sensores y se revisaran los protocolos más famosos. Así mismo, se examinara la identificación por radiofrecuencia (RFID) ya que se está convirtiendo en algo actual y su presencia importante. La RFID tiene un papel crucial que desempeñar en el futuro en el mundo de los negocios y los individuos por igual. El impacto mundial que ha tenido la identificación sin cables está ejerciendo fuertes presiones en la tecnología RFID, los servicios de investigación y desarrollo, desarrollo de normas, el cumplimiento de la seguridad y la privacidad y muchos más. Su potencial económico se ha demostrado en algunos países mientras que otros están simplemente en etapas de planificación o en etapas piloto, pero aun tiene que afianzarse o desarrollarse a través de la modernización de los modelos de negocio y aplicaciones para poder tener un mayor impacto en la sociedad. Las posibles aplicaciones de redes de sensores son de interés para la mayoría de campos. La monitorización ambiental, la guerra, la educación infantil, la vigilancia, la micro-cirugía y la agricultura son solo unos pocos ejemplos de los muchísimos campos en los que tienen cabida las redes mencionadas anteriormente. Estados Unidos de América es probablemente el país que más ha investigado en esta área por lo que veremos muchas soluciones propuestas provenientes de ese país. Universidades como Berkeley, UCLA (Universidad de California, Los Ángeles) Harvard y empresas como Intel lideran dichas investigaciones. Pero no solo EE.UU. usa e investiga las redes de sensores inalámbricos. La Universidad de Southampton, por ejemplo, está desarrollando una tecnología para monitorear el comportamiento de los glaciares mediante redes de sensores que contribuyen a la investigación fundamental en glaciología y de las redes de sensores inalámbricos. Así mismo, Coalesenses GmbH (Alemania) y Zurich ETH están trabajando en diversas aplicaciones para redes de sensores inalámbricos en numerosas áreas. Una solución española será la elegida para ser examinada más a fondo por ser innovadora, adaptable y polivalente. Este estudio del sensor se ha centrado principalmente en aplicaciones de tráfico, pero no se puede olvidar la lista de más de 50 aplicaciones diferentes que ha sido publicada por la firma creadora de este sensor específico. En la actualidad hay muchas tecnologías de vigilancia de vehículos, incluidos los sensores de bucle, cámaras de video, sensores de imagen, sensores infrarrojos, radares de microondas, GPS, etc. El rendimiento es aceptable, pero no suficiente, debido a su limitada cobertura y caros costos de implementación y mantenimiento, especialmente este ultimo. Tienen defectos tales como: línea de visión, baja exactitud, dependen mucho del ambiente y del clima, no se puede realizar trabajos de mantenimiento sin interrumpir las mediciones, la noche puede condicionar muchos de ellos, tienen altos costos de instalación y mantenimiento, etc. Por consiguiente, en las aplicaciones reales de circulación, los datos recibidos son insuficientes o malos en términos de tiempo real debido al escaso número de detectores y su costo. Con el aumento de vehículos en las redes viales urbanas las tecnologías de detección de vehículos se enfrentan a nuevas exigencias. Las redes de sensores inalámbricos son actualmente una de las tecnologías más avanzadas y una revolución en la detección de información remota y en las aplicaciones de recogida. Las perspectivas de aplicación en el sistema inteligente de transporte son muy amplias. Con este fin se ha desarrollado un programa de localización de objetivos y recuento utilizando una red de sensores binarios. Esto permite que el sensor necesite mucha menos energía durante la transmisión de información y que los dispositivos sean más independientes con el fin de tener un mejor control de tráfico. La aplicación se centra en la eficacia de la colaboración de los sensores en el seguimiento más que en los protocolos de comunicación utilizados por los nodos sensores. Las operaciones de salida y retorno en las vacaciones son un buen ejemplo de por qué es necesario llevar la cuenta de los coches en las carreteras. Para ello se ha desarrollado una simulación en Matlab con el objetivo localizar objetivos y contarlos con una red de sensores binarios. Dicho programa se podría implementar en el sensor que Libelium, la empresa creadora del sensor que se examinara concienzudamente, ha desarrollado. Esto permitiría que el aparato necesitase mucha menos energía durante la transmisión de información y los dispositivos sean más independientes. Los prometedores resultados obtenidos indican que los sensores de proximidad binarios pueden formar la base de una arquitectura robusta para la vigilancia de áreas amplias y para el seguimiento de objetivos. Cuando el movimiento de dichos objetivos es suficientemente suave, no tiene cambios bruscos de trayectoria, el algoritmo ClusterTrack proporciona un rendimiento excelente en términos de identificación y seguimiento de trayectorias los objetos designados como blancos. Este algoritmo podría, por supuesto, ser utilizado para numerosas aplicaciones y se podría seguir esta línea de trabajo para futuras investigaciones. No es sorprendente que las redes de sensores de binarios de proximidad hayan atraído mucha atención últimamente ya que, a pesar de la información mínima de un sensor de proximidad binario proporciona, las redes de este tipo pueden realizar un seguimiento de todo tipo de objetivos con la precisión suficiente. Abstract The increasing interest in wireless sensor networks can be promptly understood simply by thinking about what they essentially are: a large number of small sensing self-powered nodes which gather information or detect special events and communicate in a wireless fashion, with the end goal of handing their processed data to a base station. The sensor nodes are densely deployed inside the phenomenon, they deploy random and have cooperative capabilities. Usually these devices are small and inexpensive, so that they can be produced and deployed in large numbers, and so their resources in terms of energy, memory, computational speed and bandwidth are severely constrained. Sensing, processing and communication are three key elements whose combination in one tiny device gives rise to a vast number of applications. Sensor networks provide endless opportunities, but at the same time pose formidable challenges, such as the fact that energy is a scarce and usually non-renewable resource. However, recent advances in low power Very Large Scale Integration, embedded computing, communication hardware, and in general, the convergence of computing and communications, are making this emerging technology a reality. Likewise, advances in nanotechnology and Micro Electro-Mechanical Systems are pushing toward networks of tiny distributed sensors and actuators. There are different sensors such as pressure, accelerometer, camera, thermal, and microphone. They monitor conditions at different locations, such as temperature, humidity, vehicular movement, lightning condition, pressure, soil makeup, noise levels, the presence or absence of certain kinds of objects, mechanical stress levels on attached objects, the current characteristics such as speed, direction and size of an object, etc. The state of Wireless Sensor Networks will be checked and the most famous protocols reviewed. As Radio Frequency Identification (RFID) is becoming extremely present and important nowadays, it will be examined as well. RFID has a crucial role to play in business and for individuals alike going forward. The impact of ‘wireless’ identification is exerting strong pressures in RFID technology and services research and development, standards development, security compliance and privacy, and many more. The economic value is proven in some countries while others are just on the verge of planning or in pilot stages, but the wider spread of usage has yet to take hold or unfold through the modernisation of business models and applications. Possible applications of sensor networks are of interest to the most diverse fields. Environmental monitoring, warfare, child education, surveillance, micro-surgery, and agriculture are only a few examples. Some real hardware applications in the United States of America will be checked as it is probably the country that has investigated most in this area. Universities like Berkeley, UCLA (University of California, Los Angeles) Harvard and enterprises such as Intel are leading those investigations. But not just USA has been using and investigating wireless sensor networks. University of Southampton e.g. is to develop technology to monitor glacier behaviour using sensor networks contributing to fundamental research in glaciology and wireless sensor networks. Coalesenses GmbH (Germany) and ETH Zurich are working in applying wireless sensor networks in many different areas too. A Spanish solution will be the one examined more thoroughly for being innovative, adaptable and multipurpose. This study of the sensor has been focused mainly to traffic applications but it cannot be forgotten the more than 50 different application compilation that has been published by this specific sensor’s firm. Currently there are many vehicle surveillance technologies including loop sensors, video cameras, image sensors, infrared sensors, microwave radar, GPS, etc. The performance is acceptable but not sufficient because of their limited coverage and expensive costs of implementation and maintenance, specially the last one. They have defects such as: line-ofsight, low exactness, depending on environment and weather, cannot perform no-stop work whether daytime or night, high costs for installation and maintenance, etc. Consequently, in actual traffic applications the received data is insufficient or bad in terms of real-time owed to detector quantity and cost. With the increase of vehicle in urban road networks, the vehicle detection technologies are confronted with new requirements. Wireless sensor network is the state of the art technology and a revolution in remote information sensing and collection applications. It has broad prospect of application in intelligent transportation system. An application for target tracking and counting using a network of binary sensors has been developed. This would allow the appliance to spend much less energy when transmitting information and to make more independent devices in order to have a better traffic control. The application is focused on the efficacy of collaborative tracking rather than on the communication protocols used by the sensor nodes. Holiday crowds are a good case in which it is necessary to keep count of the cars on the roads. To this end a Matlab simulation has been produced for target tracking and counting using a network of binary sensors that e.g. could be implemented in Libelium’s solution. Libelium is the enterprise that has developed the sensor that will be deeply examined. This would allow the appliance to spend much less energy when transmitting information and to make more independent devices. The promising results obtained indicate that binary proximity sensors can form the basis for a robust architecture for wide area surveillance and tracking. When the target paths are smooth enough ClusterTrack particle filter algorithm gives excellent performance in terms of identifying and tracking different target trajectories. This algorithm could, of course, be used for different applications and that could be done in future researches. It is not surprising that binary proximity sensor networks have attracted a lot of attention lately. Despite the minimal information a binary proximity sensor provides, networks of these sensing modalities can track all kinds of different targets classes accurate enough.

A hierarchical strategy for real-time tracking on-board UAVs

In this paper, we present a real-time tracking strategy based on direct methods for tracking tasks on-board UAVs, that is able to overcome problems posed by the challenging conditions of the task: e.g. constant vibrations, fast 3D changes, and limited capacity on-board. The vast majority of approaches make use of feature-based methods to track objects. Nonetheless, in this paper we show that although some of these feature-based solutions are faster, direct methods can be more robust under fast 3D motions (fast changes in position), some changes in appearance, constant vibrations (without requiring any specific hardware or software for video stabilization), and situations where part of the object to track is out the field of view of the camera. The performance of the proposed strategy is evaluated with images from real-flight tests using different evaluation mechanisms (e.g. accurate position estimation using a Vicon sytem). Results show that our tracking strategy performs better than well known feature-based algorithms and well known configurations of direct methods, and that the recovered data is robust enough for vision-in-the-loop tasks.

Cognitive neurorehabilitation based on interactive video technology

Cognitive impairment is the main cause of disability in developed societies. New interactive technologies help therapists in neurorehabilitation in order to increase patients’ autonomy and quality of life. This work proposes Interactive Video (IV) as a technology to develop cognitive rehabilitation tasks based on Activities of Daily Living (ADL). ADL cognitive task has been developed and integrated with eye-tracking technology for task interaction and patients’ performance monitoring.

EVA: Endoscopic Video Analysis of the surgical scene for the assessment of MIS psychomotor skills

The present work covers the first validation efforts of the EVA Tracking System for the assessment of minimally invasive surgery (MIS) psychomotor skills. Instrument movements were recorded for 42 surgeons (4 expert, 22 residents, 16 novice medical students) and analyzed for a box trainer peg transfer task. Construct validation was established for 7/9 motion analysis parameters (MAPs). Concurrent validation was determined for 8/9 MAPs against the TrEndo Tracking System. Finally, automatic determination of surgical proficiency based on the MAPs was sought by 3 different approaches to supervised classification (LDA, SVM, ANFIS), with accuracy results of 61.9%, 83.3% and 80.9% respectively. Results not only reflect on the validation of EVA for skills? assessment, but also on the relevance of motion analysis of instruments in the determination of surgical competence.

A Hierarchical Tracking Strategy for Vision-Based Applications On-Board UAVs

In this paper, we apply a hierarchical tracking strategy of planar objects (or that can be assumed to be planar) that is based on direct methods for vision-based applications on-board UAVs. The use of this tracking strategy allows to achieve the tasks at real-time frame rates and to overcome problems posed by the challenging conditions of the tasks: e.g. constant vibrations, fast 3D changes, or limited capacity on-board. The vast majority of approaches make use of feature-based methods to track objects. Nonetheless, in this paper we show that although some of these feature-based solutions are faster, direct methods can be more robust under fast 3D motions (fast changes in position), some changes in appearance, constant vibrations (without requiring any specific hardware or software for video stabilization), and situations in which part of the object to track is outside of the field of view of the camera. The performance of the proposed tracking strategy on-board UAVs is evaluated with images from realflight tests using manually-generated ground truth information, accurate position estimation using a Vicon system, and also with simulated data from a simulation environment. Results show that the hierarchical tracking strategy performs better than wellknown feature-based algorithms and well-known configurations of direct methods, and that its performance is robust enough for vision-in-the-loop tasks, e.g. for vision-based landing tasks.

Multi-resolution model-based traffic sign detection and tracking

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.