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The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations

informatietechnologie --- Computer. Automation --- informatica --- Operational research. Game theory --- grafische vormgeving --- Artificial intelligence. Robotics. Simulation. Graphics --- multimedia --- stochastische analyse --- Computer vision. --- Computer science. --- Multimedia systems. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- User Interfaces and Human Computer Interaction. --- Multimedia Information Systems. --- Probability and Statistics in Computer Science. --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Informatics --- Science --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Optical data processing. --- User interfaces (Computer systems). --- Multimedia information systems. --- Mathematical statistics. --- Interfaces, User (Computer systems) --- Human-machine systems --- Human-computer interaction --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Optical equipment --- Statistical methods --- Machine learning.

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Human-Computer Interaction (HCI) lies at the crossroads of many scienti?c areas including arti?cial intelligence, computer vision, face recognition, motion tracking, etc. In order for HCI systems to interact seamlessly with people, they need to understand their environment through vision and auditory input. Mo- over, HCI systems should learn how to adaptively respond depending on the situation. The goal of this workshop was to bring together researchers from the ?eld of computer vision whose work is related to human-computer interaction. The selected articles for this workshop address a wide range of theoretical and - plication issues in human-computer interaction ranging from human-robot - teraction, gesture recognition, and body tracking, to facial features analysis and human-computer interaction systems. This year 74 papers from 18 countries were submitted and 22 were accepted for presentation at the workshop after being reviewed by at least 3 members of the Program Committee. We had therefore a very competitive acceptance rate of less than 30% and as a consequence we had a very-high-quality workshop. Wewouldliketo thankallmembersofthe ProgramCommitteefor their help in ensuring the quality of the papers accepted for publication. We are grateful to Dr. Jian Wang for giving the keynote address. In addition, we wish to thank the organizers of the 10th IEEE International Conference on Computer Vision and our sponsors, University of Amsterdam, Leiden Institute of Advanced Computer Science, and the University of Illinois at Urbana-Champaign, for support in setting up our workshop.

Mathematical statistics --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- factoranalyse --- grafische vormgeving --- informatica --- KI (kunstmatige intelligentie)

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Human-Computer Interaction (HCI) lies at the crossroads of many scienti?c areas including arti?cial intelligence, computer vision, face recognition, motion tracking, etc. In order for HCI systems to interact seamlessly with people, they need to understand their environment through vision and auditory input. Mo- over, HCI systems should learn how to adaptively respond depending on the situation. The goal of this workshop was to bring together researchers from the ?eld of computer vision whose work is related to human-computer interaction. The selected articles for this workshop address a wide range of theoretical and - plication issues in human-computer interaction ranging from human-robot - teraction, gesture recognition, and body tracking, to facial features analysis and human-computer interaction systems. This year 74 papers from 18 countries were submitted and 22 were accepted for presentation at the workshop after being reviewed by at least 3 members of the Program Committee. We had therefore a very competitive acceptance rate of less than 30% and as a consequence we had a very-high-quality workshop. Wewouldliketo thankallmembersofthe ProgramCommitteefor their help in ensuring the quality of the papers accepted for publication. We are grateful to Dr. Jian Wang for giving the keynote address. In addition, we wish to thank the organizers of the 10th IEEE International Conference on Computer Vision and our sponsors, University of Amsterdam, Leiden Institute of Advanced Computer Science, and the University of Illinois at Urbana-Champaign, for support in setting up our workshop.

Computer vision --- Computer software --- Vision par ordinateur --- Logiciels --- Congresses. --- Human factors --- Congrès --- Facteurs humains --- Congresses --- Human-computer interaction --- Applied Physics --- Engineering & Applied Sciences --- Computer science. --- User interfaces (Computer systems). --- Computer graphics. --- Image processing. --- Pattern recognition. --- Computer Science. --- User Interfaces and Human Computer Interaction. --- Image Processing and Computer Vision. --- Computer Graphics. --- Pattern Recognition. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Image processing --- Interfaces, User (Computer systems) --- Human-machine systems --- Informatics --- Science --- Digital techniques --- Computer vision. --- Optical pattern recognition. --- Pattern perception --- Perceptrons --- Visual discrimination --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Integrated optics --- Photonics --- Computers --- Optical equipment