IR @ Goa University

Collaborative representation with hole filling techniques for Kinect RGB-D face recognition

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dc.contributor.author Gaonkar, A.A.
dc.contributor.author Vetrekar, N.T.
dc.contributor.author Gad, R.S.
dc.date.accessioned 2023-09-27T07:04:17Z
dc.date.available 2023-09-27T07:04:17Z
dc.date.issued 2023
dc.identifier.citation International Journal of Biometrics. 15(2); 2023; 170-193. en_US
dc.identifier.uri https://doi.org/10.1504/IJBM.2023.129223
dc.identifier.uri http://irgu.unigoa.ac.in/drs/handle/unigoa/7114
dc.description.abstract We present in this paper, three different filtering techniques based on kernel function to fill missing information in depth map images obtained from low resolution sensor such as Kinect to improve the performance accuracy of RGB-D face recognition systems. We propose in this study, an RGB-D face recognition scheme that combines depth map and colour image using wavelet average fusion followed by collaborative representation classifier (CRC) for comparison of reference and probe images. We present the evaluation results based on our GU-RGBD face database and IIIT-D face database to present the significance of our three different filters employed in hole filling. Further, our investigation presents an extensive experimental analysis using eight different feature extraction techniques independently across three different filters to demonstrate the potential of our proposed approach. The proposed approach of hole filling, improves the performance accuracy of RGB-D face recognition as compared to without employing filtering operations. en_US
dc.publisher Inderscience en_US
dc.subject Electronics en_US
dc.title Collaborative representation with hole filling techniques for Kinect RGB-D face recognition en_US
dc.type Journal article en_US
dc.identifier.impf cs


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