Tracking the motion of human hands
Humans use their hands in most of their everyday life activities. Thus, the development of technical systems that track the 3D position, orientation and full articulation of human hands from markerless visual observations can be of fundamental importance in supporting a number of diverse applications. In this talk, we provide an overview of our work
on hand tracking. First, we describe methods for vision-based detection and tracking of hands and fingers in 2D, with emphasis on occlusions handling and illumination invariance. We also demonstrate hand posture recognition techniques and their use in HCI and HRI. Then, we focus on a recently proposed framework for exploiting markerless visual observations to track the 3D position, orientation and full articulation of a human hand that moves in isolation in front of an RGBD camera. We treat this as an optimization problem that is effectively solved using a variant of Particle Swarm Optimization (PSO). Next, we show how the core of the tracking framework has been employed to provide state-of-the-art solutions for problems of even higher dimensionality and complexity, e.g., for tracking two strongly interacting hands or for tracking the state of a complex scene where a hand interacts with several objects. Finally, we demonstrate how the results of hand tracking have been used to recognize human actions and infer human intentions in the context of tabletop object manipulation scenarios.
Antonis Argyros is an Associate Professor at the Computer Science Department, University of Crete and a researcher at the Institute of Computer Science (ICS), Foundation for Research and Technology-Hellas (FORTH) in Heraklion, Crete, Greece. He received a B.Sc. degree in Computer Science (1989) and a M.Sc. degree in Computer Science (1992), both from the Computer Science Department, University of Crete. On July 1996, he completed his PhD on visual motion analysis at the same Department. He has been a postdoctoral fellow at the Computational Vision and Active Perception Laboratory (CVAP) at the Royal Institute of Technology in Stockholm, Sweden. Since 1999, as a member of the Computational Vision and Robotics Laboratory (CVRL) of FORTH-ICS, he has been involved in many RTD projects in computer vision, image analysis and robotics. He is an area editor for the Computer Vision and Image Understanding Journal (CVIU), member of the Editorial Board of the IET Image Processing Journal and one of the general chairs of the 11th European Conference in Computer Vision (ECCV'2010, Heraklion, Crete). He is also a faculty member of the Brain and Mind interdisciplinary graduate program and a member of the Strategy Task Group of the European Consortium for Informatics and Mathematics (ERCIM). The research interests of Argyros fall in the areas of computer vision with emphasis on tracking, human gesture and posture recognition, 3D reconstruction and omnidirectional vision. He is also interested in applications of computational vision in the fields of robotics and smart environments.