{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:41:44Z","timestamp":1760240504984,"version":"build-2065373602"},"reference-count":61,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2019,7,3]],"date-time":"2019-07-03T00:00:00Z","timestamp":1562112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61571332","61261130587"],"award-info":[{"award-number":["61571332","61261130587"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Motion segmentation is aimed at segmenting the feature point trajectories belonging to independently moving objects. Using the affine camera model, the motion segmentation problem can be viewed as a subspace clustering problem\u2014clustering the data points drawn from a union of low-dimensional subspaces. In this paper, we propose a solution for motion segmentation that uses a multi-model fitting technique. We propose a data grouping method and a model selection strategy for obtaining more distinguishable data point permutation preferences, which significantly improves the clustering. We perform extensive testing on the Hopkins 155 dataset, and two real-world datasets. The experimental results illustrate that the proposed method can deal with incomplete trajectories and the perspective effect, comparing favorably with the current state of the art.<\/jats:p>","DOI":"10.3390\/s19132936","type":"journal-article","created":{"date-parts":[[2019,7,3]],"date-time":"2019-07-03T11:14:49Z","timestamp":1562152489000},"page":"2936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Motion Segmentation Based on Model Selection in Permutation Space for RGB Sensors"],"prefix":"10.3390","volume":"19","author":[{"given":"Xi","family":"Zhao","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Information Engineering in Surveying, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianqing","family":"Qin","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Information Engineering in Surveying, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Luo","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Information Engineering in Surveying, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,3]]},"reference":[{"key":"ref_1","first-page":"398","article-title":"Motion segmentation: A review","volume":"184","author":"Zappella","year":"2008","journal-title":"Front. 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