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In this article, we propose a novel nonlinear algorithm for tracking significant deformable objects. The proposed tracking scheme has two filters. On one hand, considering that Grassmann manifold is one of entropy manifold in Lie group manifold, which can describe and process the data of appearance feature more accurately, one filter is designed on it, to estimate the object appearance, by making full use of the transformation relationship between the point on manifold and its corresponding point on tangent space. On the other hand, considering that the process of objects imaging is essentially projection transformation process, the other filter is designed on projection transformation (SL(3)) group, describing the geometric deformation of the objects. The two filters execute alternatively to mitigate tracking drift. Extensive experiments prove that the proposed method can realize stable and accurate tracking for targets with significant geometric deformation, even obscured and illumination changes. <\/jats:p>","DOI":"10.1177\/1550147718766856","type":"journal-article","created":{"date-parts":[[2018,3,28]],"date-time":"2018-03-28T09:52:28Z","timestamp":1522230748000},"page":"155014771876685","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Tracking objects using Grassmann manifold appearance modeling based on wireless multimedia sensor networks"],"prefix":"10.1177","volume":"14","author":[{"given":"Yinghong","family":"Xie","sequence":"first","affiliation":[{"name":"College of Information Engineering, Shenyang University, Shenyang, China"},{"name":"School of Electronic Information Engineering, Tianjin University, Tianjin, 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