Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance Systemopen access
- Authors
- Jung, Jaehoon; Yoon, Inhye; Paik, Joonki
- Issue Date
- Jul-2016
- Publisher
- MDPI AG
- Keywords
- occlusion detection; automatic camera calibration; depth estimation; moving object detection; video surveillance system
- Citation
- SENSORS, v.16, no.7
- Journal Title
- SENSORS
- Volume
- 16
- Number
- 7
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/6786
- DOI
- 10.3390/s16070982
- ISSN
- 1424-8220
1424-8220
- Abstract
- This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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