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Sensors 2016, 16(7), 982; doi:10.3390/s16070982

Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

1
Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea
2
ADAS Camera Team, LG Electronics, 322 Gyeongmyeong-daero, Seo-gu, Incheon 22744, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 3 May 2016 / Revised: 16 June 2016 / Accepted: 23 June 2016 / Published: 25 June 2016
(This article belongs to the Special Issue Imaging: Sensors and Technologies)
View Full-Text   |   Download PDF [24948 KB, uploaded 25 June 2016]   |  

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. View Full-Text
Keywords: occlusion detection; automatic camera calibration; depth estimation; moving object detection; video surveillance system occlusion detection; automatic camera calibration; depth estimation; moving object detection; video surveillance system
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Jung, J.; Yoon, I.; Paik, J. Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System. Sensors 2016, 16, 982.

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