- 권한신청
- P-ISSN1738-6764
- E-ISSN2093-7504
- KCI
ISSN : 1738-6764
Tracking of Multiple Vehicles Using Occlusion Segmentation Based on Spatio-Temporal Association
김수형 (전남대학교)
이귀상 (전남대학교)
양형정 (전남대학교)
나인섭 (전남대학교)
Abstract
This paper proposes a segmentation method for overlapped vehicles based on analysis of the vehicle location and the spatiotemporal association information. This method can be used in an intelligent transport system. In the proposed method, occlusion is detected by analyzing the association information based on a vehicle’s location in continuous images, and occlusion segmentation is carried out by using the vehicle information prior to occlusion. In addition, the size variations of the vehicle to which association tracking is applied can be anticipated by learning the variations according to the overlapped vehicles’ movements. To assess the performance of the suggested method, image data collected from CCTVs recording traffic information is used, and average success rate of occlusion segmentation is 96.9%.
- keywords
- Intelligent Transport System, Occlusion segmentation, Spatio-temporal association, Tracking, Vehicle.
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