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              <text>An Efficient HOG-Centroid Descriptor for Human Gait Recognition</text>
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              <text>Centroid; Descriptor; Feature fusion; Gait; HOG; Silhouette</text>
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              <text>Automatic recognition of human gait have gained much attention nowadays. Histogram of Oriented Gradient (HOG) is a widely adopted descriptor for object's shape analysis. In this paper, combination of HOG descriptor with silhouette centroid for human gait recognition is proposed. The resultant descriptor, namely HOG-Centroid, achieves better recognition performance on comparison with HOG descriptor individually as well as other existing gait recognition methods. Experiments are carried out with CASIA gait dataset B and cumulative matching scores of 95.3%, 98.1% and 99.2% are obtained for rank 1, rank 5 and rank 10 respectively.  2019 IEEE.</text>
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              <text>Sugandhi K.; Raju G.</text>
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              <text>Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019, pp. 355-360.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2019-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/AICAI.2019.8701366" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/AICAI.2019.8701366&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISBN: 978-153869346-9</text>
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              <text>English</text>
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              <text>Sugandhi K., Department of Information Technology, Kannur University, Kannur, Kerala, 670567, India; Raju G., Department of CSE, Christ (Deemed to Be University), Bengaluru, Karnataka, 560764, India</text>
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