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Title: Enhancing the robustness of skin-based face detection schemes through a visual attention architecture
Authors: Tsapatsoulis, Nicolas 
Rapantzikos, Konstantinos 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Image processing;Visualization;Computer architecture;Face--Identification
Issue Date: 2005
Source: IEEE International Conference on Image Processing, 11-14 September 2005, Genova
Conference: IEEE International Conference on Image Processing 
Abstract: Bottom up approaches to visual attention (VA) have been applied successfully in a variety of applications, where no domain information exists, e.g. general purpose image and video segmentation. In face detection, humans perform conscious search; therefore, bottom up approaches are not so efficient. In this paper we introduce the inclusion of two channels in the VA architecture proposed by Itti et al. (1998) to account for motion and conscious search in a scene. Increasing the channels in the architecture requires an efficient way of combining the various maps that are produced. We solve this problem by using an innovative committee machine scheme which allows for dynamically changing the committee members (maps) and weighting the maps according to the confidence level of their estimation. The overall VA architecture achieves significantly better results compared with the simple skin based face detection as shown in the experimental results
DOI: 10.1109/ICIP.2005.1530301
Rights: © IEEE
Type: Conference Papers
Affiliation : National Technical University Of Athens 
University of Cyprus 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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