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    ARTICLE

    Gender Recognition Based on Computer Vision System

    Li-Hong Juanga, Ming-Ni Wub, Shin-An Linb

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 249-256, 2018, DOI:10.1080/10798587.2016.1272777

    Abstract Detecting human gender from complex background, illumination variations and objects under computer vision system is very difficult but important for an adaptive information service. In this paper, a preliminary design and some experimental results of gender recognition will be presented from the walking movement that utilizes the gait-energy image (GEI) with denoised energy image (DEI) pre-processing as a machine learning support vector machine (SVM) classifier to train and extract its characteristics. The results show that the proposed method can adopt some characteristic values and the accuracy can reach up to 100% gender recognition rate under More >

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