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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1789

Title: A Real-time Model for Multiple Human Face Tracking from Low-resolution Surveillance Videos
Authors: Sarkar, R
Bakshi, S
Sa, Pankaj K
Keywords: real-time face tracking
skin detection
eye detection
mouth detection
Issue Date: Oct-2012
Publisher: Elsevier Ltd
Citation: 2nd International Conference on Communication, Computing, and Security (ICCCS 2012), 06-08 October 2012
Abstract: This article discusses a novel approach of multiple-face tracking from low-resolution surveillance videos. There has been significant research in the field of face detection using neural-network based training. Neural network based face detection methods are highly accurate, albeit computationally intensive. Hence neural network based approaches are not suitable for real-time applications. The proposed approach approximately detects faces in an image solely using the color information. It detects skin region in an image and finds existence of eye and mouth region in the skin region. If it finds so, it marks the skin region as a face and fits an oriented rectangle to the face. The approach requires low computation and hence can be applied on subsequent frames from a video. The proposed approach is tested on FERET face database images, on different images containing multiple faces captured in unconstrained environments, and on frames extracted from IP surveillance camera.
Description: Copyright for this paper belongs to Elsevier Ltd
URI: http://hdl.handle.net/2080/1789
Appears in Collections:Conference Papers

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