The study of human motion dates back more than 2000 years. With the event of information technology, new areas have been added to this field. Research using computer vision and computer graphics contributes to a transformation of biomechanics into a discipline that now applies computing technology throughout. On the other hand, computer vision and computer graphics also benefit from defining goals aimed at solving problems in biomechanics. Besides interactions, all three areas also developed their own inherent research dynamics towards studying human motion.
Researchers from all three of these areas have contributed to this book to promote the establishment of human motion research as a multi-facetted discipline and to improve the exchange of ideas and concepts between these three areas. Some chapters review the state-of-the-art whilst others report on leading edge research results, with applications in medicine, sport science, cinematography and robotics.
Researchers or students in biomechanics, computer vision or computer graphics (in a general sense, not only those working immediately on human motion), people applying results of human motion research in their disciplines, and a general audience interested in progress in science
Table of contents
1 Understanding Human Motion: A Historic Review, R. Klette, C. Tee.- Part I 2D tracking. 2 The Role of Manifold Learning in Human Motion Analysis, A. Elgammal, Chan-Su Lee. 3 Recognition of Action as a Bayesian Parameter Estimation Problem over Time, V. Kruger. 4 The William Harvey Code: Mathematical Analysis of Optical Flow Computation for Cardiac Motion, Y. Kameda, A. Imiya. 5 Detection and Tracking of Humans in Single View Sequences Using 2D Articulated Model, F. Kort, V. Hlavd!.- Part II Learning. 6 Combining Discrete and Continuous 3D Trackers, C. Tsechpenakis, D. Metaxas, C. Neidle. 7 Graphical Models for Human Motion Modeling, Kooksang Moon, V. Paviovic. 8 3D Human Motion Analysis in Monocular Video Techniques and Challenges, C. Sminchisescu. 9 Spatially and Temporally Segmenting Movement to Recognize Actions, R. Green. 10 Topologically Constrained Isometric Embedding, G. Rosman, A.M. Bronstein, M.M. Bronstein, R. Kimmel.- Part III 2D-3D tracking. 11 Contours, Optic Flow, and Prior Knowledge: Cues for Capturing 3D Human Motion in Videos, T. Brox, B. Rosenhahn, D. Cremers.