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.

Effects of camera aperture correction on keying and compositing of broadcast video

This contribution discusses the effects of camera aperture correction in broadcast video on colour-based keying. The aperture correction is used to ’sharpen’ an image and is one element that distinguishes the ’TV-look’ from ’film-look’. ’If a very high level of sharpening is applied, as is the case in many TV productions then this significantly shifts the colours around object boundaries with hight contrast. This paper discusses these effects and their impact on keying and describes a simple low-pass filter to compensate for them. Tests with colour-based segmentation algorithms show that the proposed compensation is an effective way of decreasing the keying artefacts on object boundaries.

Impact Study of Nonverbal Facial Cues on Spontaneous Chatting with Virtual Humans

Non-verbal communication (NVC) is considered to represent more than 90 percent of everyday communication. In virtual world, this important aspect of interaction between virtual humans (VH) is strongly neglected. This paper presents a user-test study to demonstrate the impact of automatically generated graphics-based NVC expression on the dialog quality: first, we wanted to compare impassive and emotion facial expression simulation for impact on the chatting. Second, we wanted to see whether people like chatting within a 3D graphical environment. Our model only proposes facial expressions and head movements induced from spontaneous chatting between VHs. Only subtle facial expressions are being used as nonverbal cues - i.e. related to the emotional model. Motion capture animations related to hand gestures, such as cleaning glasses, were randomly used to make the virtual human lively. After briefly introducing the technical architecture of the 3D-chatting system, we focus on two aspects of chatting through VHs. First, what is the influence of facial expressions that are induced from text dialog? For this purpose, we exploited an emotion engine extracting an emotional content from a text and depicting it into a virtual character developed previously [GAS11]. Second, as our goal was not addressing automatic generation of text, we compared the impact of nonverbal cues in conversation with a chatbot or with a human operator with a wizard of oz approach. Among main results, the within group study -involving 40 subjects- suggests that subtle facial expressions impact significantly not only on the quality of experience but also on dialog understanding.

The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.

Sonic intelligence as a virtual therapeutic environment

This paper reports on the results of a research project, on comparing one virtual collaborative environment with a first-person visual immersion (first-perspective interaction) and a second one where the user interacts through a sound-kinetic virtual representation of himself (avatar), as a stress-coping environment in real-life situations. Recent developments in coping research are proposing a shift from a trait-oriented approach of coping to a more situation-specific treatment. We defined as real-life situation a target-oriented situation that demands a complex coping skills inventory of high self-efficacy and internal or external "locus of control" strategies. The participants were 90 normal adults with healthy or impaired coping skills, 25-40 years of age, randomly spread across two groups. There was the same number of participants across groups and gender balance within groups. All two groups went through two phases. In Phase I, Solo, one participant was assessed using a three-stage assessment inspired by the transactional stress theory of Lazarus and the stress inoculation theory of Meichenbaum. In Phase I, each participant was given a coping skills measurement within the time course of various hypothetical stressful encounters performed in two different conditions and a control group. In Condition A, the participant was given a virtual stress assessment scenario relative to a first-person perspective (VRFP). In Condition B, the participant was given a virtual stress assessment scenario relative to a behaviorally realistic motion controlled avatar with sonic feedback (VRSA). In Condition C, the No Treatment Condition (NTC), the participant received just an interview. In Phase II, all three groups were mixed and exercised the same tasks but with two participants in pairs. The results showed that the VRSA group performed notably better in terms of cognitive appraisals, emotions and attributions than the other two groups in Phase I (VRSA, 92%; VRFP, 85%; NTC, 34%). In Phase II, the difference again favored the VRSA group against the other two. These results indicate that a virtual collaborative environment seems to be a consistent coping environment, tapping two classes of stress: (a) aversive or ambiguous situations, and (b) loss or failure situations in relation to the stress inoculation theory. In terms of coping behaviors, a distinction is made between self-directed and environment-directed strategies. A great advantage of the virtual collaborative environment with the behaviorally enhanced sound-kinetic avatar is the consideration of team coping intentions in different stages. Even if the aim is to tap transactional processes in real-life situations, it might be better to conduct research using a sound-kinetic avatar based collaborative environment than a virtual first-person perspective scenario alone. The VE consisted of two dual-processor PC systems, a video splitter, a digital camera and two stereoscopic CRT displays. The system was programmed in C++ and VRScape Immersive Cluster from VRCO, which created an artificial environment that encodes the user's motion from a video camera, targeted at the face of the users and physiological sensors attached to the body.

Ruler Based Automatic C-Arm Image Stitching Without Overlapping Constraint

In this paper, we propose a new method for stitching multiple fluoroscopic images taken by a C-arm instrument. We employ an X-ray radiolucent ruler with numbered graduations while acquiring the images, and the image stitching is based on detecting and matching ruler parts in the images to the corresponding parts of a virtual ruler. To achieve this goal, we first detect the regular spaced graduations on the ruler and the numbers. After graduation labeling, for each image, we have the location and the associated number for every graduation on the ruler. Then, we initialize the panoramic X-ray image with the virtual ruler, and we “paste” each image by aligning the detected ruler part on the original image, to the corresponding part of the virtual ruler on the panoramic image. Our method is based on ruler matching but without the requirement of matching similar feature points in pairwise images, and thus, we do not necessarily require overlap between the images. We tested our method on eight different datasets of X-ray images, including long bones and a complete spine. Qualitative and quantitative experiments show that our method achieves good results.

Face Lift Surgery for Reconstructed Virtual Humans

We introduce an innovative, semi-automatic method to transform low resolution facial meshes into high definition ones, based on the tailoring of a generic, neutral human head model, designed by an artist, to fit the facial features of a specific person. To determine these facial features we need to select a set of "control points" (corners of eyes, lips, etc.) in at least two photographs of the subject's face. The neutral head mesh is then automatically reshaped according to the relation between the control points in the original subject's mesh through a set of transformation pyramids. The last step consists in merging both meshes and filling the gaps that appear in the previous process. This algorithm avoids the use of expensive and complicated technologies to obtain depth maps, which also need to be meshed later.

RECLAMO: virtual and collaborative honeynets based on trust management and autonomous systems applied to intrusion management

Security intrusions in large systems is a problem due to its lack of scalability with the current IDS-based approaches. This paper describes the RECLAMO project, where an architecture for an Automated Intrusion Response System (AIRS) is being proposed. This system will infer the most appropriate response for a given attack, taking into account the attack type, context information, and the trust and reputation of the reporting IDSs. RECLAMO is proposing a novel approach: diverting the attack to a specific honeynet that has been dynamically built based on the attack information. Among all components forming the RECLAMO's architecture, this paper is mainly focused on defining a trust and reputation management model, essential to recognize if IDSs are exposing an honest behavior in order to accept their alerts as true. Experimental results confirm that our model helps to encourage or discourage the launch of the automatic reaction process.

Refined facial disparity maps for automatic creation of 3D avatars

We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimation strategies to obtain a coarse initial disparity map, and SIFT to detect and match several feature points in the subjects face. We then use these points as anchors to modify the disparity in the facial area by building a Delaunay triangulation of their convex hull and interpolating their disparity values inside each triangle. We thus obtain a refined disparity map providing a much more accurate representation of the the subjects facial features. This refined facial disparity map may be easily transformed, through the camera calibration parameters, into a depth map to be used, also automatically, to improve the facial mesh of a 3D avatar to match the subjects real human features.

Bayesian scene analysis for multi-camera 3D tracking and camera positioning

Los sistemas de seguimiento mono-cámara han demostrado su notable capacidad para el análisis de trajectorias de objectos móviles y para monitorización de escenas de interés; sin embargo, tanto su robustez como sus posibilidades en cuanto a comprensión semántica de la escena están fuertemente limitadas por su naturaleza local y monocular, lo que los hace insuficientes para aplicaciones realistas de videovigilancia. El objetivo de esta tesis es la extensión de las posibilidades de los sistemas de seguimiento de objetos móviles para lograr un mayor grado de robustez y comprensión de la escena. La extensión propuesta se divide en dos direcciones separadas. La primera puede considerarse local, ya que está orientada a la mejora y enriquecimiento de las posiciones estimadas para los objetos móviles observados directamente por las cámaras del sistema; dicha extensión se logra mediante el desarrollo de un sistema multi-cámara de seguimiento 3D, capaz de proporcionar consistentemente las posiciones 3D de múltiples objetos a partir de las observaciones capturadas por un conjunto de sensores calibrados y con campos de visión solapados. La segunda extensión puede considerarse global, dado que su objetivo consiste en proporcionar un contexto global para relacionar las observaciones locales realizadas por una cámara con una escena de mucho mayor tamaño; para ello se propone un sistema automático de localización de cámaras basado en las trayectorias observadas de varios objetos móviles y en un mapa esquemático de la escena global monitorizada. Ambas líneas de investigación se tratan utilizando, como marco común, técnicas de estimación bayesiana: esta elección está justificada por la versatilidad y flexibilidad proporcionada por dicho marco estadístico, que permite la combinación natural de múltiples fuentes de información sobre los parámetros a estimar, así como un tratamiento riguroso de la incertidumbre asociada a las mismas mediante la inclusión de modelos de observación específicamente diseñados. Además, el marco seleccionado abre grandes posibilidades operacionales, puesto que permite la creación de diferentes métodos numéricos adaptados a las necesidades y características específicas de distintos problemas tratados. El sistema de seguimiento 3D con múltiples cámaras propuesto está específicamente diseñado para permitir descripciones esquemáticas de las medidas realizadas individualmente por cada una de las cámaras del sistema: esta elección de diseño, por tanto, no asume ningún algoritmo específico de detección o seguimiento 2D en ninguno de los sensores de la red, y hace que el sistema propuesto sea aplicable a redes reales de vigilancia con capacidades limitadas tanto en términos de procesamiento como de transmision. La combinación robusta de las observaciones capturadas individualmente por las cámaras, ruidosas, incompletas y probablemente contaminadas por falsas detecciones, se basa en un metodo de asociación bayesiana basado en geometría y color: los resultados de dicha asociación permiten el seguimiento 3D de los objetos de la escena mediante el uso de un filtro de partículas. El sistema de fusión de observaciones propuesto tiene, como principales características, una gran precisión en términos de localización 3D de objetos, y una destacable capacidad de recuperación tras eventuales errores debidos a un número insuficiente de datos de entrada. El sistema automático de localización de cámaras se basa en la observación de múltiples objetos móviles y un mapa esquemático de las áreas transitables del entorno monitorizado para inferir la posición absoluta de dicho sensor. Para este propósito, se propone un novedoso marco bayesiano que combina modelos dinámicos inducidos por el mapa en los objetos móviles presentes en la escena con las trayectorias observadas por la cámara, lo que representa un enfoque nunca utilizado en la literatura existente. El sistema de localización se divide en dos sub-tareas diferenciadas, debido a que cada una de estas tareas requiere del diseño de algoritmos específicos de muestreo para explotar en profundidad las características del marco desarrollado: por un lado, análisis de la ambigüedad del caso específicamente tratado y estimación aproximada de la localización de la cámara, y por otro, refinado de la localización de la cámara. El sistema completo, diseñado y probado para el caso específico de localización de cámaras en entornos de tráfico urbano, podría tener aplicación también en otros entornos y sensores de diferentes modalidades tras ciertas adaptaciones. ABSTRACT Mono-camera tracking systems have proved their capabilities for moving object trajectory analysis and scene monitoring, but their robustness and semantic possibilities are strongly limited by their local and monocular nature and are often insufficient for realistic surveillance applications. This thesis is aimed at extending the possibilities of moving object tracking systems to a higher level of scene understanding. The proposed extension comprises two separate directions. The first one is local, since is aimed at enriching the inferred positions of the moving objects within the area of the monitored scene directly covered by the cameras of the system; this task is achieved through the development of a multi-camera system for robust 3D tracking, able to provide 3D tracking information of multiple simultaneous moving objects from the observations reported by a set of calibrated cameras with semi-overlapping fields of view. The second extension is global, as is aimed at providing local observations performed within the field of view of one camera with a global context relating them to a much larger scene; to this end, an automatic camera positioning system relying only on observed object trajectories and a scene map is designed. The two lines of research in this thesis are addressed using Bayesian estimation as a general unifying framework. Its suitability for these two applications is justified by the flexibility and versatility of that stochastic framework, which allows the combination of multiple sources of information about the parameters to estimate in a natural and elegant way, addressing at the same time the uncertainty associated to those sources through the inclusion of models designed to this end. In addition, it opens multiple possibilities for the creation of different numerical methods for achieving satisfactory and efficient practical solutions to each addressed application. The proposed multi-camera 3D tracking method is specifically designed to work on schematic descriptions of the observations performed by each camera of the system: this choice allows the use of unspecific off-the-shelf 2D detection and/or tracking subsystems running independently at each sensor, and makes the proposal suitable for real surveillance networks with moderate computational and transmission capabilities. The robust combination of such noisy, incomplete and possibly unreliable schematic descriptors relies on a Bayesian association method, based on geometry and color, whose results allow the tracking of the targets in the scene with a particle filter. The main features exhibited by the proposal are, first, a remarkable accuracy in terms of target 3D positioning, and second, a great recovery ability after tracking losses due to insufficient input data. The proposed system for visual-based camera self-positioning uses the observations of moving objects and a schematic map of the passable areas of the environment to infer the absolute sensor position. To this end, a new Bayesian framework combining trajectory observations and map-induced dynamic models for moving objects is designed, which represents an approach to camera positioning never addressed before in the literature. This task is divided into two different sub-tasks, setting ambiguity analysis and approximate position estimation, on the one hand, and position refining, on the other, since they require the design of specific sampling algorithms to correctly exploit the discriminative features of the developed framework. This system, designed for camera positioning and demonstrated in urban traffic environments, can also be applied to different environments and sensors of other modalities after certain required adaptations.

Rediseño del tutor automático de un laboratorio virtual

El siguiente trabajo abarca todo el proceso llevado a cabo para el rediseño de un sistema automático de tutoría que se integra con laboratorios virtuales desarrollados para la realización de prácticas por parte de estudiantes dentro de entornos virtuales tridimensionales. Los principales objetivos de este rediseño son la mejora del rendimiento del sistema automático de tutoría, haciéndolo más eficiente y por tanto permitiendo a un mayor número de estudiantes realizar una práctica al mismo tiempo. Además, este rediseño permitirá que el tutor se pueda integrar con otros motores gráficos con un coste relativamente bajo. Se realiza en primer lugar una introducción a los principales conceptos manejados en este trabajo así como algunos aspectos relacionados con trabajos previos a este rediseño del tutor automático, concretamente la versión anterior del tutor ligada a la plataforma OpenSim. Acto seguido se detallarán qué requisitos funcionales cumplirá así como las ventajas que aportará este nuevo diseño. A continuación, se explicará el desarrollo del trabajo donde se podrá ver cómo se ha reestructurado el antiguo sistema de tutoría, la aplicación de un diseño orientado a objetos y los distintos paquetes y clases que lo conforman. Por último, se detallarán las conclusiones obtenidas durante el desarrollo del trabajo así como la implicación del trabajo aquí mostrado en futuros desarrollos.---ABSTRACT--- The following work shows the process that has been carried out in order to redesign an automatic tutoring system that can be integrated into virtual laboratories developed for supporting students’ practices in 3D virtual environments. The main goals of this redesign are the improvement of automatic tutoring system performance, making it more efficient and therefore allowing more students to perform a practice at the same time. Furthermore, this redesign allows the tutor to be integrated with other graphic engines with a relative low cost. Firstly, we begin with an introduction to the main concepts used in this work and some aspects concerning the related previous works to this automatic tutoring system redesign, such as the previous version of the tutoring system bound to OpenSim. Secondly, it will be detailed what functional requirements are met and what advantages this new tutoring system will provide. Next, it will be explained how this work has been developed, how the previous tutoring system has been restructured, how an object-oriented design is applied and the classes and packages derived from this design. Finally, it will be outlined the conclusions drawn in the development of this work as well as how this work will take part in future works.

Bayesian scene analysis for multi-camera 3D tracking and camera positioning

Los sistemas de seguimiento mono-cámara han demostrado su notable capacidad para el análisis de trajectorias de objectos móviles y para monitorización de escenas de interés; sin embargo, tanto su robustez como sus posibilidades en cuanto a comprensión semántica de la escena están fuertemente limitadas por su naturaleza local y monocular, lo que los hace insuficientes para aplicaciones realistas de videovigilancia. El objetivo de esta tesis es la extensión de las posibilidades de los sistemas de seguimiento de objetos móviles para lograr un mayor grado de robustez y comprensión de la escena. La extensión propuesta se divide en dos direcciones separadas. La primera puede considerarse local, ya que está orientada a la mejora y enriquecimiento de las posiciones estimadas para los objetos móviles observados directamente por las cámaras del sistema; dicha extensión se logra mediante el desarrollo de un sistema multi-cámara de seguimiento 3D, capaz de proporcionar consistentemente las posiciones 3D de múltiples objetos a partir de las observaciones capturadas por un conjunto de sensores calibrados y con campos de visión solapados. La segunda extensión puede considerarse global, dado que su objetivo consiste en proporcionar un contexto global para relacionar las observaciones locales realizadas por una cámara con una escena de mucho mayor tamaño; para ello se propone un sistema automático de localización de cámaras basado en las trayectorias observadas de varios objetos móviles y en un mapa esquemático de la escena global monitorizada. Ambas líneas de investigación se tratan utilizando, como marco común, técnicas de estimación bayesiana: esta elección está justificada por la versatilidad y flexibilidad proporcionada por dicho marco estadístico, que permite la combinación natural de múltiples fuentes de información sobre los parámetros a estimar, así como un tratamiento riguroso de la incertidumbre asociada a las mismas mediante la inclusión de modelos de observación específicamente diseñados. Además, el marco seleccionado abre grandes posibilidades operacionales, puesto que permite la creación de diferentes métodos numéricos adaptados a las necesidades y características específicas de distintos problemas tratados. El sistema de seguimiento 3D con múltiples cámaras propuesto está específicamente diseñado para permitir descripciones esquemáticas de las medidas realizadas individualmente por cada una de las cámaras del sistema: esta elección de diseño, por tanto, no asume ningún algoritmo específico de detección o seguimiento 2D en ninguno de los sensores de la red, y hace que el sistema propuesto sea aplicable a redes reales de vigilancia con capacidades limitadas tanto en términos de procesamiento como de transmision. La combinación robusta de las observaciones capturadas individualmente por las cámaras, ruidosas, incompletas y probablemente contaminadas por falsas detecciones, se basa en un metodo de asociación bayesiana basado en geometría y color: los resultados de dicha asociación permiten el seguimiento 3D de los objetos de la escena mediante el uso de un filtro de partículas. El sistema de fusión de observaciones propuesto tiene, como principales características, una gran precisión en términos de localización 3D de objetos, y una destacable capacidad de recuperación tras eventuales errores debidos a un número insuficiente de datos de entrada. El sistema automático de localización de cámaras se basa en la observación de múltiples objetos móviles y un mapa esquemático de las áreas transitables del entorno monitorizado para inferir la posición absoluta de dicho sensor. Para este propósito, se propone un novedoso marco bayesiano que combina modelos dinámicos inducidos por el mapa en los objetos móviles presentes en la escena con las trayectorias observadas por la cámara, lo que representa un enfoque nunca utilizado en la literatura existente. El sistema de localización se divide en dos sub-tareas diferenciadas, debido a que cada una de estas tareas requiere del diseño de algoritmos específicos de muestreo para explotar en profundidad las características del marco desarrollado: por un lado, análisis de la ambigüedad del caso específicamente tratado y estimación aproximada de la localización de la cámara, y por otro, refinado de la localización de la cámara. El sistema completo, diseñado y probado para el caso específico de localización de cámaras en entornos de tráfico urbano, podría tener aplicación también en otros entornos y sensores de diferentes modalidades tras ciertas adaptaciones. ABSTRACT Mono-camera tracking systems have proved their capabilities for moving object trajectory analysis and scene monitoring, but their robustness and semantic possibilities are strongly limited by their local and monocular nature and are often insufficient for realistic surveillance applications. This thesis is aimed at extending the possibilities of moving object tracking systems to a higher level of scene understanding. The proposed extension comprises two separate directions. The first one is local, since is aimed at enriching the inferred positions of the moving objects within the area of the monitored scene directly covered by the cameras of the system; this task is achieved through the development of a multi-camera system for robust 3D tracking, able to provide 3D tracking information of multiple simultaneous moving objects from the observations reported by a set of calibrated cameras with semi-overlapping fields of view. The second extension is global, as is aimed at providing local observations performed within the field of view of one camera with a global context relating them to a much larger scene; to this end, an automatic camera positioning system relying only on observed object trajectories and a scene map is designed. The two lines of research in this thesis are addressed using Bayesian estimation as a general unifying framework. Its suitability for these two applications is justified by the flexibility and versatility of that stochastic framework, which allows the combination of multiple sources of information about the parameters to estimate in a natural and elegant way, addressing at the same time the uncertainty associated to those sources through the inclusion of models designed to this end. In addition, it opens multiple possibilities for the creation of different numerical methods for achieving satisfactory and efficient practical solutions to each addressed application. The proposed multi-camera 3D tracking method is specifically designed to work on schematic descriptions of the observations performed by each camera of the system: this choice allows the use of unspecific off-the-shelf 2D detection and/or tracking subsystems running independently at each sensor, and makes the proposal suitable for real surveillance networks with moderate computational and transmission capabilities. The robust combination of such noisy, incomplete and possibly unreliable schematic descriptors relies on a Bayesian association method, based on geometry and color, whose results allow the tracking of the targets in the scene with a particle filter. The main features exhibited by the proposal are, first, a remarkable accuracy in terms of target 3D positioning, and second, a great recovery ability after tracking losses due to insufficient input data. The proposed system for visual-based camera self-positioning uses the observations of moving objects and a schematic map of the passable areas of the environment to infer the absolute sensor position. To this end, a new Bayesian framework combining trajectory observations and map-induced dynamic models for moving objects is designed, which represents an approach to camera positioning never addressed before in the literature. This task is divided into two different sub-tasks, setting ambiguity analysis and approximate position estimation, on the one hand, and position refining, on the other, since they require the design of specific sampling algorithms to correctly exploit the discriminative features of the developed framework. This system, designed for camera positioning and demonstrated in urban traffic environments, can also be applied to different environments and sensors of other modalities after certain required adaptations.

Especificación del comportamiento de un avatar en un mundo virtual mediante una ontología

El presente trabajo describe la construcción de una aplicación que controla a un Non Player Character (NPC), en un mundo virtual. La aplicación desarrollada, que tiene como nombre BotManager, realiza dos tareas fundamentales: 1) conectarse al repositorio de conocimiento, que en esta implementación es una ontología expresada en OWL, para obtener las acciones que debe realizar el NPC dentro del mundo virtual; y 2) ordenar al NPC que realice estas acciones en un mundo virtual creado con la plataforma OpenSimulator. BotManager puede tener variadas aplicaciones, por lo tanto puede ser usada como complemento en mundos virtuales aplicados a la educación, simulación, ocio, etc. Ahora bien, la principal razón que motivó el desarrollo del BotManager fue la de crear un sistema de demostración automática de tareas en un mundo virtual destinado a la educación/ entrenamiento. De esta forma, un Sistema Inteligente de Tutoría integrado con un mundo virtual podría demostrar paso a paso a un estudiante cómo realizar una tarea en el mundo virtual. La ontología que lee el BotManager extiende la ontología propuesta en la tesis “Una propuesta de modelado del estudiante basada en ontologías y diagnóstico pedagógico-cognitivo no monótono” de Julia Parraga en el 2011 (Ontología de Julia). La construcción y las pruebas del BotManager se llevaron a cabo en tres etapas: 1) creación de la Ontología de Acciones del NPC que extiende la Ontología de Julia; 2) diseño e implementación de la aplicación en C# que lee la ontología que contiene el plan de acción del NPC, y ordena al NPC realizar las acciones en el mundo virtual; y 3) pruebas de la aplicación con la práctica “preparación de una taza de cafe”, que es parte de un Laboratorio Virtual de Biotecnología. El BotManager se ha diseñado como una aplicación cliente que se conecta a un servidor de Open- Simulator. Por lo tanto, puede ejecutarse en una máquina distinta a la del servidor. Asimismo, en la implementación del BotManager se ha utilizado una librería gratuita denominada LibOpenMetaverse que permite controlar un NPC de forma remota.---ABSTRACT---This paper describes the construction of an application that controls a Non Player Character (NPC), in a virtual world. The application developed, called BotManager, performs two main tasks: 1) the connection to the repository of knowledge, which in this implementation is an ontology expressed in OWL, and retrieving the actions to be performed by the NPC within the virtual world; and 2) commanding the NPC to perform these actions in a virtual world created with the OpenSimulator platform. BotManager can have diverse applications, therefore it can be used as a complement in virtual worlds applied to education, simulation, entertainment, etc. However, the main reason behind the development of BotManager was to create an automatic demonstration of tasks in a virtual world for education / training. Thus, a virtual world integrated with an Intelligent Tutoring Systems could demonstrate step by step to a student how to perform a task in the virtual world. The ontology used by the BotManager extends ontology proposed in the thesis “A proposal for modeling ontologies based student and not monotonous teaching-cognitive diagnosis” by Julia Parraga in 2011 (Julia’s Ontology). Construction and testing of BotManager were conducted in three stages: 1) creation of the NPC Actions Ontology by extending the Julia’s Ontology; 2) design and implementation of the application in C# that reads the ontology containing the plan of action of the NPC, and commands the NPC to perform the read plan in the virtual world; and 3) testing of the application with the practice “preparing a cup of coffee”, which is part of a Virtual Laboratory of Biotechnology. The BotManager has been designed as a client application that connects to an OpenSimulator server. Therefore, it can run on a different machine to the server. To implement the BotManager we have used a free library called libopenmetaverse that allows us to control a NPC remotely.

Statistical moving object detection for mobile devices with camera

A novel and high-quality system for moving object detection in sequences recorded with moving cameras is proposed. This system is based on the collaboration between an automatic homography estimation module for image alignment, and a robust moving object detection using an efficient spatiotemporal nonparametric background modeling.

Architecture to Support Automatic Grading Processes in Programming Teaching

La calificación automática de tareas de programación es un tema importante dentro del campo de la innovación educativa que se enfoca en mejorar las habilidades de programación de los estudiantes y en optimizar el tiempo que el profesorado dedica a ello. Uno de los principales problemas vigentes está relacionado con la diversidad de criterios para calificar las tareas de programación. El presente trabajo propone e implementa una arquitectura, basada en el concepto de orquestación de servicios, para soportar varios procesos de calificación automática de tareas de programación. Esto es obtenido a través de las características de modularidad, extensibilidad y flexibilidad que la arquitectura provee al proceso de calificación. La arquitectura define como pieza clave un elemento llamado Grading-submodule, el mismo que provee un servicio de evaluación del código fuente considerando un criterio de calificación. La implementación se ha llevado a cabo sobre la herramienta Virtual Programming Lab; y los resultados demuestran la factibilidad de realización, y la utilidad tanto para el profesorado como para los estudiantes.