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Quality based frame selection for video face recognition

Anantharajah, Kaneswaran, Denman, Simon, Sridharan, Sridha, Fookes, Clinton B., & Tjondronegoro, Dian W. (2012) Quality based frame selection for video face recognition. In Proceedings of 6th International Conference on Signal Processing and Communication Systems (ICSPCS'2012), IEEE Xplore, Gold Coast, Qld.

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    Abstract

    Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.

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    ID Code: 54336
    Item Type: Conference Paper
    Keywords: Face Recognition, Gabor, Neural Network
    Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000)
    Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
    Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
    Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
    Australian and New Zealand Standard Research Classification
    Divisions: Current > Schools > School of Electrical Engineering & Computer Science
    Current > Schools > School of Information Systems
    Past > Institutes > Information Security Institute
    Current > QUT Faculties and Divisions > Science & Engineering Faculty
    Copyright Owner: Copyright 2012 please consult the authors
    Deposited On: 29 Oct 2012 10:19
    Last Modified: 11 Apr 2014 10:18

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