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Abnormal Posture Detection in an Omni-directional-camera-based Surveillance System

Din-Chang Tseng and Chien-Hung Chen
The Institute of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan
Abstract—In various general environments, the aged or disabled people may fall, squat, or sit down on ground due to sick or dysfunction in move. If the events are unable discovered in time, the fatal danger may be then caused. To reduce the fatal events, an environmental monitoring system for the aged or disabled people is proposed. In this study, four kinds of posture detection are considered in the proposed system: (i) fall down and crouch, (ii) going out a room without permission, (iii) leaving specified area without permission, and (iv) recording walk trajectory. An omni-directional camera is used to capture images for monitoring. The background subtraction method is first applied to extract targets. Then principal component analysis (PCA) and the change of height of a personal trapezoidal bounding box are used to detect fall down and crouch postures. Several experiments on various environments based on the proposed approach were conducted and evaluated. Stable detection results were obtained to show the feasibility of the proposed system.

Index Terms—surveillance system, abnormal posture detection, omni-directional camera, principal component analysis

Cite: Din-Chang Tseng and Chien-Hung Chen, "Abnormal Posture Detection in an Omni-directional-camera-based Surveillance System," Jounal of Automation and Control Engineering, Vol. 4, No. 6, pp. 367-375, December, 2016. doi: 10.18178/joace.4.6.367-375
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