Tracking Human Motion From Monocular Sequences

Abstract

In recent years, analysis of human motion has become an increasingly relevant research topic with applications as diverse as animation, virtual reality, security, and advanced human-machine interfaces. In particular, motion capture systems are well known nowadays since they are used in the movie industry. These systems require expensive multicamera setups or markers to be worn by the user. This paper describes an attempt to provide a markerless low cost and real-time solution for home users. We propose a novel approach for robust detection and tracking of the user's body joints that exploits different algorithms as different sources of information and fuses their estimates with particle filters. This system may be employed for real-time animation of VRML or X3D avatars using an off-the-shelf digital camera and a standard PC.

A Multimodal Learning System for Individuals with Sensorial, Neuropsychological, and Relational Impairments

“…There are several high-level tracking systems which try to track and/or estimate in real-time the 2D positions of the joints of the human body. They use statistical models of the background and foreground to segment the image into blobs [20]. Two examples of well-known methods are represented by the Pfinder [21] and 4 [22] systems.…”