ROI sensitive analysis for real time gender classification

RODRIGUES, Marcos, KORMANN, Mariza and TOMEK, Peter (2014). ROI sensitive analysis for real time gender classification. In: MASTORAKIS, Nikos, PSARRIS, Kleanthis, VACHTSEVANOS, George, DONDON, Philippe, MLADENOV, Valeri, BULUCEA, Aida, RUDA, Imre and MARTIN, Olga, (eds.) Advances in information sciences and applications : Proceedings of 18th International Conference on Computers (part of CSCC'14). Recent advances in computer engineering series, 1 (22). World Scientific and Engineering Academy and Society (WSEAS), 87-90.

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This paper addresses the issue of real time gender classification through texture analysis. The purpose is to perform sensitivity analysis over a number of ROI-Regions of Interest defined over face images. The determination of the smaller ROI yielding robust classification results will be used for fast computation of texture parameters allowing gender classification to operate in real-time. Results demonstrate that the ROI comprising the front and the region of the eyes is the most reliable achieving classification accuracy of 88% for both male and female subjects using raw data and non-optimised extraction and classification algorithms. This is a significant result that will drive future research on optimisation of texture extraction and linear discriminant algorithms.

Item Type: Book Section
Additional Information: Paper originally presented at the 18th International Conference on Computers (part of the Circuits, Systems, Communications and Computers) held at Santorini Island, Greece, July 17-21, 2014
Research Institute, Centre or Group: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
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Depositing User: Marcos Rodrigues
Date Deposited: 21 Jul 2014 11:18
Last Modified: 21 Aug 2015 05:36

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