Speaker: Dr. Fatih Porikli, Mitsubishi Electric Research Laboratory (MERL)
Date: Wednesday, March 5 2008
Time: 3:00PM to 4:00PM Refreshments: 2:45PM
Location: Star Seminar Room (32-D463)
Host: C. Mario Christoudias, Gerald Dalley, MIT CSAIL
Contact: C. Mario Christoudias, Gerald Dalley, 3-4278, 3-6095, cmch@csail.mit.edu , dalleyg@mit.edu
Object detection and tracking, as our eyes do so innately, are among the most challenging tasks in computer vision. In general, natural objects belong to same class exhibit a large variance in their appearance. Besides, varying imaging conditions, partial occlusions, non-rigid shape deformations, multifaceted profiles and insufficient image resolutions make the detection more difficult. Similarly, a tracked object may undergo severe appearance transformations, suddenly change its motion, become fully occluded, congregate into a group of identical objects, etc. Traditional approaches tend to address these issues separately, often out of context by aiming for fixed generic solutions. Recently, there is push towards making use of any useful bit of information embedded in priori and contextual cues. More systems seek to provide online adaptation to local conditions. In this talk, various aspects of the conventional and contextual detection and tracking methods will be dissected and a unifying statistical descriptor will be examined.
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