3D object reconstruction using computer vision : reconstruction and characterization applications for external human anatomical structures

Tese de doutoramento. Engenharia Informática. Faculdade de Engenharia. Universidade do Porto. 201

Real-time Immersive human-computer interaction based on tracking and recognition of dynamic hand gestures

With fast developing and ever growing use of computer based technologies, human-computer interaction (HCI) plays an increasingly pivotal role. In virtual reality (VR), HCI technologies provide not only a better understanding of three-dimensional shapes and spaces, but also sensory immersion and physical interaction. With the hand based HCI being a key HCI modality for object manipulation and gesture based communication, challenges are presented to provide users a natural, intuitive, effortless, precise, and real-time method for HCI based on dynamic hand gestures, due to the complexity of hand postures formed by multiple joints with high degrees-of-freedom, the speed of hand movements with highly variable trajectories and rapid direction changes, and the precision required for interaction between hands and objects in the virtual world. Presented in this thesis is the design and development of a novel real-time HCI system based on a unique combination of a pair of data gloves based on fibre-optic curvature sensors to acquire finger joint angles, a hybrid tracking system based on inertia and ultrasound to capture hand position and orientation, and a stereoscopic display system to provide an immersive visual feedback. The potential and effectiveness of the proposed system is demonstrated through a number of applications, namely, hand gesture based virtual object manipulation and visualisation, hand gesture based direct sign writing, and hand gesture based finger spelling. For virtual object manipulation and visualisation, the system is shown to allow a user to select, translate, rotate, scale, release and visualise virtual objects (presented using graphics and volume data) in three-dimensional space using natural hand gestures in real-time. For direct sign writing, the system is shown to be able to display immediately the corresponding SignWriting symbols signed by a user using three different signing sequences and a range of complex hand gestures, which consist of various combinations of hand postures (with each finger open, half-bent, closed, adduction and abduction), eight hand orientations in horizontal/vertical plans, three palm facing directions, and various hand movements (which can have eight directions in horizontal/vertical plans, and can be repetitive, straight/curve, clockwise/anti-clockwise). The development includes a special visual interface to give not only a stereoscopic view of hand gestures and movements, but also a structured visual feedback for each stage of the signing sequence. An excellent basis is therefore formed to develop a full HCI based on all human gestures by integrating the proposed system with facial expression and body posture recognition methods. Furthermore, for finger spelling, the system is shown to be able to recognise five vowels signed by two hands using the British Sign Language in real-time

Globally-Coordinated Locally-Linear Modeling of Multi-Dimensional Data

This thesis considers the problem of modeling and analysis of continuous, locally-linear, multi-dimensional spatio-temporal data. Our work extends the previously reported theoretical work on the global coordination model to temporal analysis of continuous, multi-dimensional data. We have developed algorithms for time-varying data analysis and used them in full-scale, real-world applications. The applications demonstrated in this thesis include tracking, synthesis, recognitions and retrieval of dynamic objects based on their shape, appearance and motion. The proposed approach in this thesis has advantages over existing approaches to analyzing complex spatio-temporal data. Experiments show that the new modeling features of our approach improve the performance of existing approaches in many applications. In object tracking, our approach is the first one to track nonlinear appearance variations by using low-dimensional representation of the appearance change in globally-coordinated linear subspaces. In dynamic texture synthesis, we are able to model non-stationary dynamic textures, which cannot be handled by any of the existing approaches. In human motion synthesis, we show that realistic synthesis can be performed without using specific transition points, or key frames

Learning Pose Invariant and Covariant Classifiers from Image Sequences

Object tracking and detection over a wide range of viewpoints is a long-standing problem in Computer Vision. Despite significant advance in wide-baseline sparse interest point matching and development of robust dense feature models, it remains a largely open problem. Moreover, abundance of low cost mobile platforms and novel application areas, such as real-time Augmented Reality, constantly push the performance limits of existing methods. There is a need to modify and adapt these to meet more stringent speed and capacity requirements. In this thesis, we aim to overcome the difficulties due to the multi-view nature of the object detection task. We significantly improve upon existing statistical keypoint matching algorithms to perform fast and robust recognition of image patches independently of object pose. We demonstrate this on various 2D and 3D datasets. The statistical keypoint matching approaches require massive amounts of training data covering a wide range of viewpoints. We have developed a weakly supervised algorithm to greatly simplify their training for 3D objects. We also integrate this algorithm in a 3D tracking-by-detection system to perform real-time Augmented Reality. Finally, we extend the use of a large training set with smooth viewpoint variation to category-level object detection. We introduce a new dataset with continuous pose annotations which we use to train pose estimators for objects of a single category. By using these estimators' output to select pose specific classifiers, our framework can simultaneously localize objects in an image and recover their pose. These decoupled pose estimation and classification steps yield improved detection rates. Overall, we rely on image and video sequences to train classifiers that can either operate independently of the object pose or recover the pose parameters explicitly. We show that in both cases our approaches mitigate the effects of viewpoint changes and improve the recognition performance

Real-time immersive human-computer interaction based on tracking and recognition of dynamic hand gestures

With fast developing and ever growing use of computer based technologies, human-computer interaction (HCI) plays an increasingly pivotal role. In virtual reality (VR), HCI technologies provide not only a better understanding of three-dimensional shapes and spaces, but also sensory immersion and physical interaction. With the hand based HCI being a key HCI modality for object manipulation and gesture based communication, challenges are presented to provide users a natural, intuitive, effortless, precise, and real-time method for HCI based on dynamic hand gestures, due to the complexity of hand postures formed by multiple joints with high degrees-of-freedom, the speed of hand movements with highly variable trajectories and rapid direction changes, and the precision required for interaction between hands and objects in the virtual world. Presented in this thesis is the design and development of a novel real-time HCI system based on a unique combination of a pair of data gloves based on fibre-optic curvature sensors to acquire finger joint angles, a hybrid tracking system based on inertia and ultrasound to capture hand position and orientation, and a stereoscopic display system to provide an immersive visual feedback. The potential and effectiveness of the proposed system is demonstrated through a number of applications, namely, hand gesture based virtual object manipulation and visualisation, hand gesture based direct sign writing, and hand gesture based finger spelling. For virtual object manipulation and visualisation, the system is shown to allow a user to select, translate, rotate, scale, release and visualise virtual objects (presented using graphics and volume data) in three-dimensional space using natural hand gestures in real-time. For direct sign writing, the system is shown to be able to display immediately the corresponding SignWriting symbols signed by a user using three different signing sequences and a range of complex hand gestures, which consist of various combinations of hand postures (with each finger open, half-bent, closed, adduction and abduction), eight hand orientations in horizontal/vertical plans, three palm facing directions, and various hand movements (which can have eight directions in horizontal/vertical plans, and can be repetitive, straight/curve, clockwise/anti-clockwise). The development includes a special visual interface to give not only a stereoscopic view of hand gestures and movements, but also a structured visual feedback for each stage of the signing sequence. An excellent basis is therefore formed to develop a full HCI based on all human gestures by integrating the proposed system with facial expression and body posture recognition methods. Furthermore, for finger spelling, the system is shown to be able to recognise five vowels signed by two hands using the British Sign Language in real-time.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Application-driven visual computing towards industry 4.0 2018

245 p.La Tesis recoge contribuciones en tres campos: 1. Agentes Virtuales Interactivos: autónomos, modulares, escalables, ubicuos y atractivos para el usuario. Estos IVA pueden interactuar con los usuarios de manera natural.2. Entornos de RV/RA Inmersivos: RV en la planificación de la producción, el diseño de producto, la simulación de procesos, pruebas y verificación. El Operario Virtual muestra cómo la RV y los Co-bots pueden trabajar en un entorno seguro. En el Operario Aumentado la RA muestra información relevante al trabajador de una manera no intrusiva. 3. Gestión Interactiva de Modelos 3D: gestión online y visualización de modelos CAD multimedia, mediante conversión automática de modelos CAD a la Web. La tecnología Web3D permite la visualización e interacción de estos modelos en dispositivos móviles de baja potencia.Además, estas contribuciones han permitido analizar los desafíos presentados por Industry 4.0. La tesis ha contribuido a proporcionar una prueba de concepto para algunos de esos desafíos: en factores humanos, simulación, visualización e integración de modelos

Automated Facial Anthropometry Over 3D Face Surface Textured Meshes

The automation of human face measurement means facing mayor technical and technological challenges. The use of 3D scanning technology is widely accepted in the scientific community and it offers the possibility of developing non-invasive measurement techniques. However, the selection of the points that form the basis of the measurements is a task that still requires human intervention. This work introduces digital image processing methods for automatic localization of facial features. The first goal was to examine different ways to represent 3D shapes and to evaluate whether these could be used as representative features of facial attributes, in order to locate them automatically. Based on the above, a non-rigid registration procedure was developed to estimate dense point-to-point correspondence between two surfaces. The method is able to register 3D models of faces in the presence of facial expressions. Finally, a method that uses both shape and appearance information of the surface, was designed for automatic localization of a set of facial features that are the basis for determining anthropometric ratios, which are widely used in fields such as ergonomics, forensics, surgical planning, among othersResumen : La automatización de la medición del rostro humano implica afrontar grandes desafíos técnicos y tecnológicos. Una alternativa de solución que ha encontrado gran aceptación dentro de la comunidad científica, corresponde a la utilización de tecnología de digitalización 3D con lo cual ha sido posible el desarrollo de técnicas de medición no invasivas. Sin embargo, la selección de los puntos que son la base de las mediciones es una tarea que aún requiere de la intervención humana. En este trabajo se presentan métodos de procesamiento digital de imágenes para la localización automática de características faciales. Lo primero que se hizo fue estudiar diversas formas de representar la forma en 3D y cómo estas podían contribuir como características representativas de los atributos faciales con el fin de poder ubicarlos automáticamente. Con base en lo anterior, se desarrolló un método para la estimación de correspondencia densa entre dos superficies a partir de un procedimiento de registro no rígido, el cual se enfocó a modelos de rostros 3D en presencia de expresiones faciales. Por último, se plantea un método, que utiliza tanto información de la forma como de la apariencia de las superficies, para la localización automática de un conjunto de características faciales que son la base para determinar índices antropométricos ampliamente utilizados en campos tales como la ergonomía, ciencias forenses, planeación quirúrgica, entre otrosDoctorad

From Image-based Motion Analysis to Free-Viewpoint Video

The problems of capturing real-world scenes with cameras and automatically analyzing the visible motion have traditionally been in the focus of computer vision research. The photo-realistic rendition of dynamic real-world scenes, on the other hand, is a problem that has been investigated in the field of computer graphics. In this thesis, we demonstrate that the joint solution to all three of these problems enables the creation of powerful new tools that are benecial for both research disciplines. Analysis and rendition of real-world scenes with human actors are amongst the most challenging problems. In this thesis we present new algorithmic recipes to attack them. The dissertation consists of three parts: In part I, we present novel solutions to two fundamental problems of human motion analysis. Firstly, we demonstrate a novel hybrid approach for markerfree human motion capture from multiple video streams. Thereafter, a new algorithm for automatic non-intrusive estimation of kinematic body models of arbitrary moving subjects from video is detailed. In part II of the thesis, we demonstrate that a marker-free motion capture approach makes possible the model-based reconstruction of free-viewpoint videos of human actors from only a handful of video streams. The estimated 3D videos enable the photo-realistic real-time rendition of a dynamic scene from arbitrary novel viewpoints. Texture information from video is not only applied to generate a realistic surface appearance, but also to improve the precision of the motion estimation scheme. The commitment to a generic body model also allows us to reconstruct a time-varying reflectance description of an actor`s body surface which allows us to realistically render the free-viewpoint videos under arbitrary lighting conditions. A novel method to capture high-speed large scale motion using regular still cameras and the principle of multi-exposure photography is described in part III. The fundamental principles underlying the methods in this thesis are not only applicable to humans but to a much larger class of subjects. It is demonstrated that, in conjunction, our proposed algorithmic recipes serve as building blocks for the next generation of immersive 3D visual media.Die Entwicklung neuer Algorithmen zur optischen Erfassung und Analyse der Bewegung in dynamischen Szenen ist einer der Forschungsschwerpunkte in der computergestützten Bildverarbeitung. Während im maschinellen Bildverstehen das Augenmerk auf der Extraktion von Informationen liegt, konzentriert sich die Computergrafik auf das inverse Problem, die fotorealistische Darstellung bewegter Szenen. In jüngster Vergangenheit haben sich die beiden Disziplinen kontinuierlich angenähert, da es eine Vielzahl an herausfordernden wissenschaftlichen Fragestellungen gibt, die eine gemeinsame Lösung des Bilderfassungs-, des Bildanalyse- und des Bildsyntheseproblems verlangen. Zwei der schwierigsten Probleme, welche für Forscher aus beiden Disziplinen eine große Relevanz besitzen, sind die Analyse und die Synthese von dynamischen Szenen, in denen Menschen im Mittelpunkt stehen. Im Rahmen dieser Dissertation werden Verfahren vorgestellt, welche die optische Erfassung dieser Art von Szenen, die automatische Analyse der Bewegungen und die realistische neue Darstellung im Computer erlauben. Es wid deutlich werden, dass eine Integration von Algorithmen zur Lösung dieser drei Probleme in ein Gesamtsystem die Erzeugung völlig neuartiger dreidimensionaler Darstellungen von Menschen in Bewegung ermöglicht. Die Dissertation ist in drei Teile gegliedert: Teil I beginnt mit der Beschreibung des Entwurfs und des Baus eines Studios zur zeitsynchronen Erfassung mehrerer Videobildströme. Die im Studio aufgezeichneten Multivideosequenzen dienen als Eingabedaten für die im Rahmen dieser Dissertation entwickelten videogestützten Bewegunsanalyseverfahren und die Algorithmen zur Erzeugung dreidimensionaler Videos. Im Anschluß daran werden zwei neu entwickelte Verfahren vorgestellt, die Antworten auf zwei fundamentale Fragen in der optischen Erfassung menschlicher Bewegung geben, die Messung von Bewegungsparametern und die Erzeugung von kinematischen Skelettmodellen. Das erste Verfahren ist ein hybrider Algorithmus zur markierungslosen optischen Messung von Bewegunsgparametern aus Multivideodaten. Der Verzicht auf optische Markierungen wird dadurch ermöglicht, dass zur Bewegungsanalyse sowohl aus den Bilddaten rekonstruierte Volumenmodelle als auch leicht zu erfassende Körpermerkmale verwendet werden. Das zweite Verfahren dient der automatischen Rekonstruktion eines kinematischen Skelettmodells anhand von Multivideodaten. Der Algorithmus benötigt weder optischen Markierungen in der Szene noch a priori Informationen über die Körperstruktur, und ist in gleicher Form auf Menschen, Tiere und Objekte anwendbar. Das Thema das zweiten Teils dieser Arbeit ist ein modellbasiertes Verfahrenzur Rekonstruktion dreidimensionaler Videos von Menschen in Bewegung aus nur wenigen zeitsynchronen Videoströmen. Der Betrachter kann die errechneten 3D Videos auf einem Computer in Echtzeit abspielen und dabei interaktiv einen beliebigen virtuellen Blickpunkt auf die Geschehnisse einnehmen. Im Zentrum unseres Ansatzes steht ein silhouettenbasierter Analyse-durch-Synthese Algorithmus, der es ermöglicht, ohne optische Markierungen sowohl die Form als auch die Bewegung eines Menschen zu erfassen. Durch die Berechnung zeitveränderlicher Oberächentexturen aus den Videodaten ist gewährleistet, dass eine Person aus jedem beliebigen Blickwinkel ein fotorealistisches Erscheinungsbild besitzt. In einer ersten algorithmischen Erweiterung wird gezeigt, dass die Texturinformation auch zur Verbesserung der Genauigkeit der Bewegunsgssch ätzung eingesetzt werden kann. Zudem ist es durch die Verwendung eines generischen Körpermodells möglich, nicht nur dynamische Texturen sondern sogar dynamische Reektionseigenschaften der Körperoberäche zu messen. Unser Reektionsmodell besteht aus einer parametrischen BRDF für jeden Texel und einer dynamischen Normalenkarte für die gesamte Körperoberäche. Auf diese Weise können 3D Videos auch unter völlig neuen simulierten Beleuchtungsbedingungen realistisch wiedergegeben werden. Teil III dieser Arbeit beschreibt ein neuartiges Verfahren zur optischen Messung sehr schneller Bewegungen. Bisher erforderten optische Aufnahmen von Hochgeschwindigkeitsbewegungen sehr teure Spezialkameras mit hohen Bildraten. Im Gegensatz dazu verwendet die hier beschriebene Methode einfache Digitalfotokameras und das Prinzip der Multiblitzfotograe. Es wird gezeigt, dass mit Hilfe dieses Verfahrens sowohl die sehr schnelle artikulierte Handbewegung des Werfers als auch die Flugparameter des Balls während eines Baseballpitches gemessen werden können. Die hochgenau erfaßten Parameter ermöglichen es, die gemessene Bewegung in völlig neuer Weise im Computer zu visualisieren. Obgleich die in dieser Dissertation vorgestellten Verfahren vornehmlich der Analyse und Darstellung menschlicher Bewegungen dienen, sind die grundlegenden Prinzipien auch auf viele anderen Szenen anwendbar. Jeder der beschriebenen Algorithmen löst zwar in erster Linie ein bestimmtes Teilproblem, aber in Ihrer Gesamtheit können die Verfahren als Bausteine verstanden werden, welche die nächste Generation interaktiver dreidimensionaler Medien ermöglichen werden

Sensor fusion in smart camera networks for ambient intelligence

This short report introduces the topics of PhD research that was conducted on 2008-2013 and was defended on July 2013. The PhD thesis covers sensor fusion theory, gathers it into a framework with design rules for fusion-friendly design of vision networks, and elaborates on the rules through fusion experiments performed with four distinct applications of Ambient Intelligence