{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:45:53Z","timestamp":1777657553636,"version":"3.51.4"},"reference-count":41,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,2,2]],"date-time":"2020-02-02T00:00:00Z","timestamp":1580601600000},"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":["61872308, 61972327, 61701191, U1605254"],"award-info":[{"award-number":["61872308, 61972327, 61701191, U1605254"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2018J01104, 2019J01026"],"award-info":[{"award-number":["2018J01104, 2019J01026"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["20720190011, 20720190063"],"award-info":[{"award-number":["20720190011, 20720190063"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"PECASE Award","award":["N00014-16-1-2254"],"award-info":[{"award-number":["N00014-16-1-2254"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Surpervoxels are becoming increasingly popular in many point cloud processing applications. However, few methods have been devised specifically for generating compact supervoxels from unstructured three-dimensional (3D) point clouds. In this study, we aimed to generate high quality over-segmentation of point clouds. We propose a merge-swap optimization framework that solves any supervoxel generation problem formulated in energy minimization. In particular, we tailored an energy function that explicitly encourages regular and compact supervoxels with adaptive size control considering local geometric information of point clouds. We also provide two acceleration techniques to reduce the computational overhead. The performance of the proposed merge-swap optimization approach is superior to that of previous work in terms of thorough optimization, computational efficiency, and practical applicability to incorporating control of other properties of supervoxels. The experiments show that our approach produces supervoxels with better segmentation quality than two state-of-the-art methods on three public datasets.<\/jats:p>","DOI":"10.3390\/rs12030473","type":"journal-article","created":{"date-parts":[[2020,2,5]],"date-time":"2020-02-05T03:18:48Z","timestamp":1580872728000},"page":"473","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Merge-Swap Optimization Framework for Supervoxel Generation from Three-Dimensional Point Clouds"],"prefix":"10.3390","volume":"12","author":[{"given":"Yanyang","family":"Xiao","sequence":"first","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen 361005, China"},{"name":"Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9960-4896","authenticated-orcid":false,"given":"Zhonggui","family":"Chen","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen 361005, China"}]},{"given":"Zhengtao","family":"Lin","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen 361005, China"}]},{"given":"Juan","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Xiamen University, Xiamen 361005, China"}]},{"given":"Yongjie Jessica","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA"}]},{"given":"Yangbin","family":"Lin","sequence":"additional","affiliation":[{"name":"Computer Engineering College, Jimei University, Xiamen 361021, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6075-796X","authenticated-orcid":false,"given":"Cheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen 361005, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1286","DOI":"10.1109\/TITS.2015.2499196","article-title":"Patch-based semantic labeling of road scene using colorized mobile LiDAR point clouds","volume":"17","author":"Luo","year":"2016","journal-title":"IEEE Trans. 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