Abstract

this paper we present a particle filter-based visual tracker that fuses three cues in a novel way: color, motion, and sound (Fig. 1). More specifically, we will introduce color as the main visual cue and fuse it, depending on the scenario under consideration, with either sound localization cues or motion activity cues. The generic objective is to track a specified object or region of interest in the sequence of images captured by the camera. We employ weak object models so as not to be too restrictive about the types of objects the algorithm can track, and to achieve robustness to large variations in the object pose, illumination, motion, etc. In this generic context, contour cues are less appropriate than color cues to characterize the visual appearance of tracked entities. The use of edge-based cues indeed requires that the class of objects to be tracked is known a priori and that rather precise silhouette models can be learned beforehand. Note however that such conditions are met in a number of tracking applications where shape cues are routinely used [2], [3], [25], [30], [40], [44], [53]

Citations