This book has two main goals: to provide a unifed and structured overview of this growing field, as well as to propose a corresponding software framework, the OpenTL library, developed by the author and his working group at TUM-Informatik. The main objective of this work is to show, how most real-world application scenarios can be naturally cast into a common description vocabulary, and therefore implemented and tested in a fully modular and scalable way, through the defnition of a layered, object-oriented software architecture.The resulting architecture covers in a seamless way all processing levels, from raw data acquisition up to model-based object detection and sequential localization, and defines, at the application level, what we call the tracking pipeline. Within this framework, extensive use of graphics hardware (GPU computing) as well as distributed processing, allows real-time performances for complex models and sensory systems.

Monocular Model-Based 3D Tracking of Rigid Objects reviews the different techniques and approaches that have been developed by industry and research.

This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios Explores the future research directions for visual tracking by analyzing the real-time applications The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

This book includes selected papers from VISIGRAPP 2007, the Joint Conference on Computer Vision and Computer Graphics, comprising two component conferences, namely, the International Conference on Computer Vision Theory and Applications (VISAPP) and the International Conference on Computer Graphics Theory and App- cations (GRAPP), held in Barcelona, Spain, during March 8–11, 2007. We received quite a high number of paper submissions: 382 in total for both conf- ences. We had contributions from more than 50 countries in all five continents. This confirms the success and global dimension of these jointly organized conferences. After a rigorous double-blind evaluation method, a total of 78 submissions were accepted as full papers. From those, 18 got selected for inclusion in this book. To ensure the sci- tific quality of the contributions, these were selected from papers that were evaluated with the highest scores by the VISIGRAPP Program Committee members and then they were extended and revised by the authors. Special thanks go to all contributors and re- rees, without whom this book would not have been possible. VISIGRAPP 2007 included four invited keynote lectures, presented by internati- ally recognized researchers. The presentations represented an important contribution to increasing the overall quality of the conference. We would like to express our - preciation to all invited keynote speakers, in alphabetical order: Jake K. Aggarwal (The University of Texas at Austin/USA), André Gagalowicz (INRIA/France), Wo- gang Heidrich (University of British Columbia/Canada), Mel Slater (Universitat Politècnica de Catalunya/Spain).

Leading scientists describe how advances in computer vision can change how we interact with computers.

We make 3-5 eye movements per second, and these movements are crucial in helping us deal with the vast amounts of information we encounter in our everyday lives. In recent years, thanks to the development of eye tracking technology, there has been a growing interest in monitoring and measuring these movements, with a view to understanding how we attend to and process the visual information we encounter Eye tracking as a research tool is now more accessible than ever, and is growing in popularity amongst researchers from a whole host of different disciplines. Usability analysts, sports scientists, cognitive psychologists, reading researchers, psycholinguists, neurophysiologists, electrical engineers, and others, all have a vested interest in eye tracking for different reasons. The ability to record eye-movements has helped advance our science and led to technological innovations. However, the growth of eye tracking in recent years has also presented a variety of challenges - in particular the issue of how to design an eye-tracking experiment, and how to analyse the data. This book is a much needed comprehensive handbook of eye tracking methodology. It describes how to evaluate and acquire an eye-tracker, how to plan and design an eye tracking study, and how to record and analyse eye-movement data. Besides technical details and theory, the heart of this book revolves around practicality - how raw data samples are converted into fixations and saccades using event detection algorithms, how the different representations of eye movement data are calculated using AOIs, heat maps and scanpaths, and how all the measures of eye movements relate to these processes. Part I presents the technology and skills needed to perform high-quality research with eye-trackers. Part II covers the predominant methods applied to the data which eye-trackers record. These include the parsing of raw sample data into oculomotor events, and how to calculate other representations of eye movements such as heat maps and transition matrices. Part III gives a comprehensive outline of the measures which can be calculated using the events and representations described in Part II. This is a taxonomy of the measures available to eye-tracking researchers, sorted by type of movement of the eyes and type of analysis. For anyone in the sciences considering conducting research involving eye-tracking, this book will be an essential reference work.

Dealing with visual perception in robots and its applications to manipulation and imitation, this monograph focuses on stereo-based methods and systems for object recognition and 6 DoF pose estimation as well as for marker-less human motion capture.