Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/1947
Title: | A committee machine scheme for feature map fusion under uncertainty: the face detection case | Authors: | Rapantzikos, Konstantinos Tsapatsoulis, Nicolas |
metadata.dc.contributor.other: | Τσαπατσούλης, Νικόλας | Major Field of Science: | Social Sciences | Keywords: | Committee machines;Map fusion;Visual attention;Face detection;Uncertainty;Image processing | Issue Date: | 1-Jun-2006 | Source: | International Journal of Intelligent Systems Technologies and Applications, 2006, vol. 1, no. 3-4, pp. 346-358 | Volume: | 1 | Issue: | 3-4 | Start page: | 346 | End page: | 358 | Journal: | International Journal of Intelligent Systems Technologies and Applications | 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: | https://hdl.handle.net/20.500.14279/1947 | DOI: | 10.1504/IJISTA.2006.009912 | Rights: | © Inderscience Enterprises | Type: | Article | Affiliation : | National Technical University Of Athens University of Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
CORE Recommender
SCOPUSTM
Citations
50
2
checked on Mar 21, 2021
Page view(s) 50
548
Last Week
1
1
Last month
4
4
checked on Dec 23, 2024
Google ScholarTM
Check
Altmetric
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.