We propose a new gait feature extraction method for gait recognition that uses the dyadic wavelet transform (DYWT) and structural similarity (SSIM). Gait recognition is a person authentication technique that uses the gait features obtained from a monitoring camera video. Most existing gait recognition methods use gait features based on the silhouette image sequence. However, the gait recognition accuracy decreases if the resolution of the silhouette image is low. We developed a new method to extract gait features from silhouette images having a low-resolution gait period sequence that uses the DYWT and SSIM. For our experiment, we prepared two types of silhouette image sequences of 100 subjects for use as the probe and gallery images, respectively. The sizes of the silhouette images were 64 × 44, 32 × 22, and 16 × 11. We describe our proposed method in detail and present our experimental results demonstrating that the extracted gait features are effective.


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    Titel :

    Gait Feature Extraction Using Dyadic Wavelet Transform and Structural Similarity for Gait Recognition


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Latifi, Shahram (Herausgeber:in) / Omura, Hajime (Autor:in) / Minamoto, Teruya (Autor:in)


    Erscheinungsdatum :

    2019-05-23


    Format / Umfang :

    5 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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