Region-of-importance detection based on fusion of audio and video

Authors:
Tao Wu;Cuong Vu;Qi Cheng;Damon M. Chandler
Affiliations:
School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK;School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK;School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK;School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK
Venue:
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Year:
2009

Citing 3
Cited 0

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Main subject detection VIA adaptive feature selection

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing

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Abstract

In this paper, a new framework is proposed for autonomous universal surveillance based on video and audio data. "Universal" indicates no specification of targets of interest. Instead, regions of importance (ROIs) in a scene should be detected. Specifically, in the video domain, a frame-based main subject detection is proposed based on adaptive selection of lowlevel features. In the audio domain, a time-delay-based direction of arrival estimation scheme is adopted. The outputs of video and audio processing are fused in a probabilistic framework to generate more refined ROIs. Experimental results demonstrate the effectiveness of the proposed scheme in ROI detection.