{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T18:24:39Z","timestamp":1776363879944,"version":"3.51.2"},"reference-count":24,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T00:00:00Z","timestamp":1642032000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2022,1,13]]},"abstract":"<jats:p>The purpose is to provide a more reliable human-computer interaction (HCI) guarantee for animation works under virtual reality (VR) technology. Inspired by artificial intelligence (AI) technology and based on the convolutional neural network\u2014support vector machine (CNN-SVM), the differences between animation works under VR technology and traditional animation works are analyzed through a comprehensive analysis of VR technology. The CNN-SVM gesture recognition algorithm using the error correction strategy is designed based on HCI recognition. To have better recognition performance, the advantages of depth image and color image are combined, and the collected information is preprocessed including the relations between the times of image training iterations and the accuracy of different methods in the direction of the test set. After experiments, the maximum accuracy of the preprocessed image can reach 0.86 showing the necessity of image preprocessing. The recognition accuracy of the optimized CNN-SVM is compared with other algorithm models. Experiments show that the accuracy of the optimized CNN-SVM has an upward trend compared with the previous CNN-SVM, and the accuracy reaches 0.97. It proves that the designed algorithm can provide good technical support for VR animation, so that VR animation works can interact well with the audience. It is of great significance for the development of VR animation and the improvement of people\u2019s artistic life quality.<\/jats:p>","DOI":"10.1155\/2022\/1712929","type":"journal-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T22:35:39Z","timestamp":1642113339000},"page":"1-8","source":"Crossref","is-referenced-by-count":37,"title":["The Path of Film and Television Animation Creation Using Virtual Reality Technology under the Artificial Intelligence"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2277-195X","authenticated-orcid":true,"given":"Xin","family":"Liu","sequence":"first","affiliation":[{"name":"School of Art and Design, Lanzhou Jiaotong University, Lanzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3766-3388","authenticated-orcid":true,"given":"Hua","family":"Pan","sequence":"additional","affiliation":[{"name":"Lanzhou Echo Creative Culture Communication Co., Ltd., Lanzhou, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.3390\/su11061605"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1007\/s11554-020-01046-y"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1007\/s12253-019-00590-8"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2939427"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1007\/s10055-018-0333-8"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.2112\/si93-088.1"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.5539\/ies.v10n7p59"},{"key":"8","first-page":"1","article-title":"A Study on effective directive technique of 3D animation in Virtual Reality-Focus on Interactive short using 3D Animation making of Unreal Engine","volume":"6","author":"J. Lee","year":"2017","journal-title":"Cartoon and Animation Studies"},{"issue":"1","key":"9","first-page":"12","article-title":"Swing: 2D and 3D animation in virtual reality work-in-progress","volume":"2","author":"M. J. 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