Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/84
Title: A committee machine scheme for feature map fusion under uncertainty: the face detection case
Authors: Rapantzikos, Konstantinos 
Tsapatsoulis, Nicolas 
Keywords: Committee machines
Map fusion
Visual attention
Face detection
Uncertainty
Image processing
Issue Date: 2006
Publisher: Inderscience Enterprises Ltd.
Source: International Journal of Intelligent Systems Technologies and Applications,Vol. 1, Nos. 3-4, 2006, Pp.346-358
Abstract: Feature map fusion in Visual Attention (VA) models is by definition an uncertain procedure. One of the major impediments in extending the static VA architecture proposed by Itti et al. (2000) to account for motion or other information is the lack of justification on how to integrate the various channels. We propose an innovative committee machine scheme that allows for dynamically changing the committee members (maps) and weighting them according to the confidence level of their estimation. Through this machine we handle the extensions on Itti's model; we add a motion channel and a prior knowledge channel which accounts for the conscious search performed by humans when looking for faces in a scene. The experimental results, obtained when considering face detection, show that the map fusion, through the proposed committee machine, leads to significantly better statistical results when compared with the simple skin-based face detection method.
URI: http://ktisis.cut.ac.cy/handle/10488/84
DOI: 10.1504/IJISTA.2006.009912
Rights: © 2006 Inderscience Enterprises Ltd.
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