Finding the Weakest Link in Person Detectors

10 years 8 months ago
Finding the Weakest Link in Person Detectors
Detecting people remains a popular and challenging problem in computer vision. In this paper, we analyze parts-based models for person detection to determine which components of their pipeline could benefit the most if improved. We accomplish this task by studying numerous detectors formed from combinations of components performed by human subjects and machines. The parts-based model we study can be roughly broken into four components: feature detection, part detection, spatial part scoring and contextual reasoning including non-maximal suppression. Our experiments conclude that part detection is the weakest link for challenging person detection datasets. Non-maximal suppression and context can also significantly boost performance. However, the use of human or machine spatial models does not significantly or consistently affect detection accuracy.
Devi Parikh, Larry Zitnick
Added 30 Mar 2011
Updated 29 Apr 2011
Type Conference
Year 2011
Where CVPR
Authors Devi Parikh, Larry Zitnick
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