Authors:
Ukyo Tanikawa
1
;
Yasutomo Kawanishi
1
;
Daisuke Deguchi
1
;
Ichiro Ide
1
;
Hiroshi Murase
1
and
Ryo Kawai
2
Affiliations:
1
Nagoya University, Japan
;
2
NEC Corporation, Japan
Keyword(s):
Object Detection, Wheelchair User, Crowded Scene, Parts-based Tracking.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
;
Video Surveillance and Event Detection
Abstract:
In recent years, there has been an increasing demand for automatic wheelchair-user detection from a surveillance
video to support wheelchair users. However, it is difficult to detect them due to occlusions by surrounding
pedestrians in a crowded scene. In this paper, we propose a detection method of wheelchair users robust to
such occlusions. Concretely, in case the detector cannot a detect wheelchair user, the proposed method estimates
his/her location by parts-based tracking based on parts relationship through time. This makes it possible
to detect occluded wheelchair users even though he/she is heavily occluded. As a result of an experiment,
the detection of wheelchair users with the proposed method achieved the highest accuracy in crowded scenes,
compared with comparative methods.