{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:02:15Z","timestamp":1760241735283,"version":"build-2065373602"},"reference-count":79,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T00:00:00Z","timestamp":1532563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["CE140100016"],"award-info":[{"award-number":["CE140100016"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, the Relative Pose based Redundancy Removal (RPRR) scheme is presented, which has been designed for mobile RGB-D sensor networks operating under bandwidth-constrained operational scenarios. The scheme considers a multiview scenario in which pairs of sensors observe the same scene from different viewpoints, and detect the redundant visual and depth information to prevent their transmission leading to a significant improvement in wireless channel usage efficiency and power savings. We envisage applications in which the environment is static, and rapid 3D mapping of an enclosed area of interest is required, such as disaster recovery and support operations after earthquakes or industrial accidents. Experimental results show that wireless channel utilization is improved by 250% and battery consumption is halved when the RPRR scheme is used instead of sending the sensor images independently.<\/jats:p>","DOI":"10.3390\/s18082430","type":"journal-article","created":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T11:32:07Z","timestamp":1532604727000},"page":"2430","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Relative Pose Based Redundancy Removal: Collaborative RGB-D Data Transmission in Mobile Visual Sensor Networks"],"prefix":"10.3390","volume":"18","author":[{"given":"Xiaoqin","family":"Wang","sequence":"first","affiliation":[{"name":"ARC Centre of Excellence for Robotic Vision, Monash University, Victoria 3800, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Y. Ahmet","family":"\u015eekercio\u011flu","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Technologie de Compi\u00e8gne, Sorbonne Universit\u00e9s, CNRS, UMR 7253 Heudiasyc-CS 60 319, 60203 Compi\u00e8gne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom","family":"Drummond","sequence":"additional","affiliation":[{"name":"ARC Centre of Excellence for Robotic Vision, Monash University, Victoria 3800, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent","family":"Fr\u00e9mont","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Technologie de Compi\u00e8gne, Sorbonne Universit\u00e9s, CNRS, UMR 7253 Heudiasyc-CS 60 319, 60203 Compi\u00e8gne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrico","family":"Natalizio","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Technologie de Compi\u00e8gne, Sorbonne Universit\u00e9s, CNRS, UMR 7253 Heudiasyc-CS 60 319, 60203 Compi\u00e8gne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isabelle","family":"Fantoni","sequence":"additional","affiliation":[{"name":"Ecole Centrale de Nantes, CNRS, UMR 6004 LS2N, 44300 Nantes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,26]]},"reference":[{"key":"ref_1","unstructured":"(2018, July 24). 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