Abstract:
Pedestrian recognition is a challenging problem in non-overlapping multi-camera object tracking. In this paper, we present a novel approach for matching pedestrians acros...View moreMetadata
Abstract:
Pedestrian recognition is a challenging problem in non-overlapping multi-camera object tracking. In this paper, we present a novel approach for matching pedestrians across non-overlapping multiple cameras without the need of a training phase or spatio-temporal cues across cameras. To deal with viewpoint changes, we introduce the concept of directional angles estimated using the spatio-temporal continuity in the single camera tracking. To deal with pose changes, a stochastic matching strategy is performed, where the similarity of two blobs belonging to different viewpoints is calculated by a novel similarity measurement algorithm. The experiments are performed on different multi-view datasets. Experimental results demonstrate the effectiveness and robustness of the proposed method.
Date of Conference: 11-14 September 2011
Date Added to IEEE Xplore: 29 December 2011
ISBN Information: