{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:49:32Z","timestamp":1750308572242,"version":"3.41.0"},"reference-count":57,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2016,3,3]],"date-time":"2016-03-03T00:00:00Z","timestamp":1456963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["3102014JC02020G07 and 3102015BJ(II)JJZ01"],"award-info":[{"award-number":["3102014JC02020G07 and 3102015BJ(II)JJZ01"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Open Research Fund of Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences"},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61105012 and 61379094"],"award-info":[{"award-number":["61105012 and 61379094"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Natural Science Foundation Research Project of Shaanxi Province","award":["2015JM6264"],"award-info":[{"award-number":["2015JM6264"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2016,3,3]]},"abstract":"<jats:p>\n            Crowd system has motivated a surge of interests in many areas of multimedia, as it contains plenty of information about crowd scenes. In crowd systems, individuals tend to exhibit collective behaviors, and the motion of all those individuals is called collective motion. As a comprehensive descriptor of collective motion,\n            <jats:italic>collectiveness<\/jats:italic>\n            has been proposed to reflect the degree of individuals moving as an entirety. Nevertheless, existing works mostly have limitations to correctly find the individuals of a crowd system and precisely capture the various relationships between individuals, both of which are essential to measure collectiveness. In this article, we propose a collectiveness-measuring method that is capable of quantifying collectiveness accurately. Our main contributions are threefold: (1) we compute relatively accurate collectiveness by making the tracked feature points represent the individuals more precisely with a point selection strategy; (2) we jointly investigate the spatial-temporal information of individuals and utilize it to characterize the topological relationship between individuals by manifold learning; (3) we propose a\n            <jats:italic>stability<\/jats:italic>\n            descriptor to deal with the irregular individuals, which influence the calculation of collectiveness. Intensive experiments on the simulated and real world datasets demonstrate that the proposed method is able to compute relatively accurate collectiveness and keep high consistency with human perception.\n          <\/jats:p>","DOI":"10.1145\/2854000","type":"journal-article","created":{"date-parts":[[2016,3,3]],"date-time":"2016-03-03T16:20:48Z","timestamp":1457022048000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Measuring Collectiveness via Refined Topological Similarity"],"prefix":"10.1145","volume":"12","author":[{"given":"Xuelong","family":"Li","sequence":"first","affiliation":[{"name":"Center for Optical Imagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Shaanxi, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mulin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Center for Optical Imagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Shaanxi, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Center for Optical Imagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Shaanxi, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2016,3,3]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.382977"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88688-4_1"},{"volume-title":"Crowd simulation modeling applied to emergency and evacuation simulations using multi-agent systems. 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