Real-time tracking for visual interface applications in cluttered and occluding situations

Abstract

Visual interface systems require object tracking techniques with real-time performance for ubiquitous interaction. A probabilistic framework for a visual tracking system, which robustly tracks targets in real-time using color and motion cues, is presented. The algorithm is based on particle filtering techniques of the I-Condensation filter. An innovation of the paper is the use of motion cues to guide the propagation of particle samples which are being evaluated using color cues. This results in a probabilistic blob tracking method which is shown to greatly outperform conventional blob trackers when in the presence of occlusion and clutter. A second innovation presented is the use of motion-based temporal signatures for the visual recognition of an initialization cue. This allows for passive initialization of the tracking system. The application presented here is the task of digital video annotation using a hand-held marking device.