A Novel Multi-planar Homography Constraint Algorithm for Robust Multi-people Location with Severe Occlusion

Multi-view approach has been proposed to solve occlusion and lack of visibility in crowded scenes. However, the problem is that too much redundancy information might bring about false alarm. Although researchers have done many efforts on how to use the multi-view information to track people accurate...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaomin Tong, Tao Yang, Runping Xi, Dapei Shao, Xiuwei Zhang
Format: Conference Proceeding
Language:English
Subjects:
Computer graphics
Computer science
Information processing
Laboratories
Layout
Object detection
Robustness
Shape
Speech processing
Target tracking
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Multi-view approach has been proposed to solve occlusion and lack of visibility in crowded scenes. However, the problem is that too much redundancy information might bring about false alarm. Although researchers have done many efforts on how to use the multi-view information to track people accurately, it is particularly hard to wipe off the false alarm. Our approach is to use multiple views cooperatively to detect objects and use objects silhouette on planes of different height to remove false alarm. To achieve this we adopt a novel multi-planar homography constraint to resolve occlusions and false alarm. Experimental results show that our algorithm is able to accurately locate people in crowded scene maintaining correct correspondences across views. Moreover, the false alarm rate is obviously reduced.
DOI:10.1109/ICIG.2009.90