{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T21:26:37Z","timestamp":1778621197458,"version":"3.51.4"},"reference-count":0,"publisher":"Sciedu Press","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIR"],"abstract":"<jats:p>Various poses, facial expressions and illuminations are the biggest challenges in the fields of face recognition. To overcome these\u00a0challenges, we propose a simple yet novel method in this paper by using the approximately symmetrical virtual face. Firstly,\u00a0based on the symmetrical characteristics of faces, we present the method to generate the virtual faces for all samples in detail.\u00a0Secondly, the collaborative representation based classification method is performed on both of the original set and virtual set\u00a0individually. In this way, two kinds of representation residuals of every class can be obtained. Thirdly, an adaptive weighted\u00a0fusion approach is presented and utilized to integrate those two kinds of representation residuals for face recognition. Lastly, we\u00a0can obtain the label of the test sample by assigning it to the class with the minimum fused residual. Several experiments are\u00a0conducted which show that the proposed method not only can greatly improve the classification accuracy, but also can effectively\u00a0reduce the negative influence of various poses, illuminations, and facial expressions.<\/jats:p>","DOI":"10.5430\/air.v6n2p69","type":"journal-article","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T02:39:34Z","timestamp":1496284774000},"page":"69","source":"Crossref","is-referenced-by-count":2,"title":["The fusion of original and symmetric virtual images for image preprocessing in face recognition and collaborative representation based classification"],"prefix":"10.5430","volume":"6","author":[{"given":"Zhaojie","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yirui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3394","published-online":{"date-parts":[[2017,6,1]]},"container-title":["Artificial Intelligence Research"],"original-title":[],"link":[{"URL":"http:\/\/www.sciedu.ca\/journal\/index.php\/air\/article\/viewFile\/11259\/7142","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/www.sciedu.ca\/journal\/index.php\/air\/article\/viewFile\/11259\/7142","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T02:39:34Z","timestamp":1496284774000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.sciedu.ca\/journal\/index.php\/air\/article\/view\/11259"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,1]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2017,2,27]]}},"URL":"https:\/\/doi.org\/10.5430\/air.v6n2p69","relation":{},"ISSN":["1927-6982","1927-6974"],"issn-type":[{"value":"1927-6982","type":"electronic"},{"value":"1927-6974","type":"print"}],"subject":[],"published":{"date-parts":[[2017,6,1]]}}}