{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T21:54:29Z","timestamp":1740174869626,"version":"3.37.3"},"reference-count":15,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T00:00:00Z","timestamp":1630886400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004607","name":"Natural Science Foundation of Guangxi Province","doi-asserted-by":"publisher","award":["2018GXNSFAA294085"],"award-info":[{"award-number":["2018GXNSFAA294085"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2021,9,6]]},"abstract":"<jats:p>In this paper, a novel approach for facial expression recognition based on sparse retained projection is proposed. The locality preserving projection (LPP) algorithm is used to reduce the dimension of face image data that ensures the local near-neighbor relationship of face images. The sparse representation method is used to solve the partial occlusion of human face and the problem of light imbalance. Through sparse reconstruction, the sparse reconstruction information of expression is retained as well as the local neighborhood information of expression, which can extract more effective and judgmental internal features from the original expression data, and the obtained projection is relatively stable. The recognition results based on CK\u2009+\u2009expression database show that this method can effectively improve the facial expression recognition rate.<\/jats:p>","DOI":"10.1155\/2021\/2658471","type":"journal-article","created":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T23:35:10Z","timestamp":1630971310000},"page":"1-10","source":"Crossref","is-referenced-by-count":1,"title":["Dynamic Facial Expression Recognition Using Sparse Reserved Projection Algorithm for Low Illumination Images"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0610-1083","authenticated-orcid":true,"given":"Hui","family":"Li","sequence":"first","affiliation":[{"name":"Guangxi University of Science and Technology, Liuzhou 545006, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.05.081"},{"first-page":"1","article-title":"Visual scene-aware hybrid neural network architecture for video-based facial expression recognition","author":"M. 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