title: Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras.
abstract: Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system.
authors.affiliation: Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea. gjslkjs@gmail.com.
authors.forename: Jaehoon
authors.initials: J
authors.lastname: Jung
authors.affiliation: Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea. inhyey@gmail.com.|ADAS Camera Team, LG Electronics, 322 Gyeongmyeong-daero, Seo-gu, Incheon 22744, Korea. inhyey@gmail.com.
authors.forename: Inhye
authors.initials: I
authors.lastname: Yoon
authors.affiliation: Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea. superlsw@gmail.com.|Software Development Team, Convergence R&amp;D Center, LG Innotek, Gyeonggi-do 15588, Korea. superlsw@gmail.com.
authors.forename: Seungwon
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea. paikj@cau.ac.kr.
authors.forename: Joonki
authors.initials: J
authors.lastname: Paik
keywords: automatic calibration; color clustering; homology; metadata descriptor; object tracking; video retrieval; video surveillance