Michael T. Chan

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We present a novel method for jointly performing recognition of complex events and linking fragmented tracks into coherent, long-duration tracks. Many event recognition methods require highly accurate tracking, and may fail when tracks corresponding to event actors are fragmented or partially missing. However, these conditions occur frequently from(More)
A good front end for visual feature extraction is an important element of audiovisual speech recognition systems. We propose a new visual feature representation that combines both geometric-and pixel-based features. Using our previously developed contour-based lip-tracking algorithm, geometric features including the height and width of the lips are(More)
Complete and accurate video tracking is very difficult to achieve in practice due to long occlusions, traffic clutter, shadows and appearance changes. In this paper, we study the feasibility of event recognition when object tracks are fragmented. By changing the lock score threshold controlling track termination, different levels of track fragmentation are(More)
We address the problems of locating, grasping, and removing one or more unknown objects from a given area. In order to accomplish the task we use HEAP, a system of coordinating the motions of the hand and arm. HEAP also includes a laser range finer, mounted at the end of a PUMA 560, allowing the system to obtain multiple views of the workspace. We obtain(More)