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ICCV
2007
IEEE

Integrating Appearance and Motion Cues for Simultaneous Detection and Segmentation of Pedestrians

11 years 1 months ago
Integrating Appearance and Motion Cues for Simultaneous Detection and Segmentation of Pedestrians
We present a unified method for simultaneously acquiring both the location and the silhouette shape of people in outdoor scenes. The proposed algorithm integrates top-down and bottom-up processes in a balanced manner, employing both appearance and motion cues at different perceptual levels. Without requiring manually segmented training data, the algorithm employs a simple top-down procedure to capture the high-level cue of object familiarity. Motivated by regularities in the shape and motion characteristics of humans, interactions among low-level contour features are exploited to extract mid-level perceptual cues such as smooth continuation, common fate, and closure. A Markov random field formulation is presented that effectively combines the various cues from the top-down and bottom-up processes. The algorithm is extensively evaluated on static and moving pedestrian datasets for both detection and segmentation.
Vinay Sharma, James W. Davis
Added 14 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 2007
Where ICCV
Authors Vinay Sharma, James W. Davis
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