{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:01:47Z","timestamp":1760608907603},"reference-count":21,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2016,6]]},"abstract":"<jats:p> We consider the problem of automatically human face recognition from frontal views with occlusion and disguise. Since the occlusion can make the query image deviated from the normal distribution, most prior block-based methods focus on reducing the occlusion influence on the global-based representation. Our method is also block-based, but the blocks are non-uniform. Each block contains a certain face component such as eyes, cheek, and forehead, which makes the block more physically meaningful. Recently, sparse representation-based classification (SRC) and Collaborative representation-based classification (CRC) are applied to image recognition successfully, so we classify each block by SRC or CRC respectively. Then the occlusion pixels can be estimated by residuals. Besides, based on the distribution of block labels and the corresponding residual, we propose a new rule for the selection of block and the coefficients for the reconstruction. The final identification is performed on the un-occluded part of each image. Experiments on the AR, extended Yale B and CMU-PIE database verify the robustness and effectiveness of our method. <\/jats:p>","DOI":"10.1142\/s0218213016500196","type":"journal-article","created":{"date-parts":[[2016,4,12]],"date-time":"2016-04-12T22:58:55Z","timestamp":1460501935000},"page":"1650019","source":"Crossref","is-referenced-by-count":4,"title":["Occluded Face Recognition Based on Block-Label and Residual"],"prefix":"10.1142","volume":"25","author":[{"given":"Shu-Huan","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Yanshan University, Qinhunagdao, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng-Ping","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Yanshan University, Qinhunagdao, P. R. 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