{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T09:25:35Z","timestamp":1772616335904,"version":"3.50.1"},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2016,2,4]],"date-time":"2016-02-04T00:00:00Z","timestamp":1454544000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Localization, which is a technique required by service robots to operate indoors, has been studied in various ways. Most localization techniques have the robot measure environmental information to obtain location information; however, this is a high-cost option because it uses extensive equipment and complicates robot development. If an external device is used to determine a robot\u2019s location and transmit this information to the robot, the cost of internal equipment required for location recognition can be reduced. This will simplify robot development. Thus, this study presents an effective method to control robots by obtaining their location information using a map constructed by visual information from surveillance cameras installed indoors. With only a single image of an object, it is difficult to gauge its size due to occlusion. Therefore, we propose a localization method using several neighboring surveillance cameras. A two-dimensional map containing robot and object position information is constructed using images of the cameras. The concept of this technique is based on modeling the four edges of the projected image of the field of coverage of the camera and an image processing algorithm of the finding object\u2019s center for enhancing the location estimation of objects of interest.  We experimentally demonstrate the effectiveness of the proposed method by analyzing the resulting movement of a robot in response to the location information obtained from the two-dimensional map. The accuracy of the multi-camera setup was measured in advance.<\/jats:p>","DOI":"10.3390\/s16020195","type":"journal-article","created":{"date-parts":[[2016,2,4]],"date-time":"2016-02-04T10:26:22Z","timestamp":1454581582000},"page":"195","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Mobile Robot Localization via Indoor Fixed Remote Surveillance Cameras"],"prefix":"10.3390","volume":"16","author":[{"given":"Jae","family":"Shim","sequence":"first","affiliation":[{"name":"Department of Mechatronics Engineering, Korea Polytechnic University, Si-Heung, Gyunggi-do 429-793, Korea"}]},{"given":"Young","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Gachon University, Sung-Nam, Gyunggi-do 461-701, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2016,2,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hopper, A., Harter, A., and Blackie, T. 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