{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T15:00:45Z","timestamp":1753887645352,"version":"3.41.2"},"reference-count":30,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T00:00:00Z","timestamp":1612742400000},"content-version":"vor","delay-in-days":38,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004884","name":"Education Department of Sichuan Province","doi-asserted-by":"publisher","award":["DM201802"],"award-info":[{"award-number":["DM201802"]}],"id":[{"id":"10.13039\/501100004884","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>On the premise of ensuring the animation effect and real\u2010time performance, it is of great significance and value for large\u2010scale group character animation synthesis how to reduce the disaster coincidence degree among various models of fast adaptive character animation synthesis. The realization method of object\u2010oriented finite state machine is studied in detail. Finite state machine (FSM) is an efficient behavior modeling method, which can describe the behavioral decisions of fast adaptive character animation synthesis in a complex virtual environment. Based on the implementation defects of the finite state machine in the traditional structure, using object\u2010oriented thinking, combined with the state design mode, we further studied a finite state machine implementation method based on object\u2010oriented technology. This achieves code reuse and simple program maintenance. The effect is extensible and effectively overcomes the shortcomings of traditional character animation synthesis. Secondly, the multipath matching tracking algorithm of the greedy algorithm is studied to generate multiple candidate sets through multiple paths, and finally, the candidate set with the minimum residual error is selected as the estimated support set, so as to improve the reconstruction performance. Further, based on the idea of multipath, using the regularization method of the ROMP algorithm, the regularized multipath matching tracking RMSP algorithm is proposed. It uses the regularized subset method to generate multiple paths and chooses the path with the fastest residual reduction as the support set of this iteration. The simulation results show that the RMSP algorithm has better reconstruction performance than the SP algorithm.<\/jats:p>","DOI":"10.1155\/2021\/6685861","type":"journal-article","created":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T23:50:05Z","timestamp":1612828205000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Fast Adaptive Character Animation Synthesis Based on Greedy Algorithm"],"prefix":"10.1155","volume":"2021","author":[{"given":"Yanqiu","family":"Zhu","sequence":"first","affiliation":[]},{"given":"Qixing","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8165-6110","authenticated-orcid":false,"given":"Xiaoying","family":"Tian","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,2,8]]},"reference":[{"key":"e_1_2_9_1_2","first-page":"268","article-title":"Design of open parking lot based on grid-segmentation and greedy-algorithm","volume":"5","author":"Wang B.","year":"2019","journal-title":"World Entific Research Journal"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.gmod.2019.101045"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10441-016-9296-x"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1002\/cav.1837"},{"key":"e_1_2_9_5_2","first-page":"449","article-title":"A high-influence greedy maximization algorithm based on community structure","volume":"11","author":"Shi H.","year":"2015","journal-title":"Journal of Computational Information Systems"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-1684(03)00111-7"},{"key":"e_1_2_9_7_2","first-page":"372","article-title":"Modal regression based greedy algorithm for robust sparse signal recovery, clustering and classification","volume":"2019","author":"Wang Y.","year":"2019","journal-title":"Neurocomputing"},{"key":"e_1_2_9_8_2","first-page":"1040","article-title":"Image segmentation using fast generalized fuzzy C-means clustering based on adaptive filtering","volume":"31","author":"Wang X.","year":"2018","journal-title":"Moshi Shibie Yu Rengong Zhineng\/Pattern Recognition and Artificial Intelligence"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2017.03.037"},{"key":"e_1_2_9_10_2","first-page":"9544","article-title":"A fast filtering method based on adaptive impulsive wavelet for the gear fault diagnosis","volume":"203","author":"Yu G.","year":"2020","journal-title":"ARCHIVE Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science"},{"key":"e_1_2_9_11_2","first-page":"010505.1","article-title":"Fast adaptive bases algorithm for non-rigid image registration","volume":"63","author":"Cheung K. 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