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In this work, an effective contour shape descriptor integrating critical points structure and Scale-invariant Heat Kernel Signature (SI-HKS) is proposed for long-distance object recognition. We firstly propose a general feature fusion model. Then, we capture the object contour structure feature with Critical-points Inner-distance Shape Context (CP-IDSC). Meanwhile, we pull-in the SI-HKS for capturing the local deformation-invariant properties of 2D shape. Based on the integration of the above two feature descriptors, the fusion descriptor is compacted by mapping into a low dimensional subspace using the bags-of-features, allowing for an efficient Bayesian classifier recognition. The extensive experiments on synthetic turbulence-degraded shapes and real-life infrared image show that the proposed method outperformed other compared approaches in terms of the recognition precision and robustness.<\/jats:p>","DOI":"10.3233\/jifs-191649","type":"journal-article","created":{"date-parts":[[2020,4,10]],"date-time":"2020-04-10T11:54:37Z","timestamp":1586519677000},"page":"3241-3257","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Long-distance deformation object recognition by integrating contour structure and scale-invariant heat kernel signature"],"prefix":"10.1177","volume":"39","author":[{"given":"Xinggui","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory on Adaptive Optics and Institute of Optics and Electronics Chinese Academy of Sciences, Chengdu, China"},{"name":"School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory on Adaptive Optics and Institute of Optics and Electronics Chinese Academy of Sciences, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Ran","sequence":"additional","affiliation":[{"name":"Key Laboratory on Adaptive Optics and Institute of Optics and Electronics Chinese Academy of Sciences, Chengdu, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Xian","sequence":"additional","affiliation":[{"name":"Key Laboratory on Adaptive Optics and Institute of Optics and Electronics Chinese Academy of Sciences, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2020,4,8]]},"reference":[{"issue":"10","key":"e_1_3_2_2_2","article-title":"Geometric distortion correction of long-range imaging containing moving objects","volume":"21","author":"Xu X.","year":"2018","unstructured":"XuX., YangP., LiuY., XianH. and XuB., Geometric distortion correction of long-range imaging containing moving objects, Journal of Optics 21(10) (2018).","journal-title":"Journal of Optics"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.07.023"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1049\/el.2010.3403"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.107010"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.70769"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2007.11.005"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.993558"},{"key":"e_1_3_2_10_2","unstructured":"SinghL.B. and HazarikaS.M. 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