{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T18:05:23Z","timestamp":1648836323376},"reference-count":12,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2006,9]]},"abstract":" This paper proposes the prediction based occluded multitarget tracking method using spatio-temporal attention mechanism. To cope with occlusion between targets, the proposed method provides an efficient method for more complex analysis by combining object association with partial probability model in spatially attentive window and occlusion activity detection in predicted temporal location. While multiple objects are moving or occluding between them in areas of visual field, a simultaneous tracking of multiple objects tends to fail. This is due to the fact that incompletely estimated feature vectors such as location, color, velocity, and acceleration of a target can provide only ambiguous and missing information. Thus, the spatially and temporally considered mechanism is proposed to track each target before, during, and after occlusion. Robustness of the proposed method is demonstrated with representative simulations. <\/jats:p>","DOI":"10.1142\/s0218001406005058","type":"journal-article","created":{"date-parts":[[2006,9,25]],"date-time":"2006-09-25T06:59:17Z","timestamp":1159167557000},"page":"925-938","source":"Crossref","is-referenced-by-count":2,"title":["PREDICTION BASED OCCLUDED MULTITARGET TRACKING USING SPATIO-TEMPORAL ATTENTION"],"prefix":"10.1142","volume":"20","author":[{"given":"HEUNGKYU","family":"LEE","sequence":"first","affiliation":[{"name":"Department of Computer Science, Department of Information and Communication Engineering, Seokyeong University, Seoul 136-704, Korea"}]},{"given":"JUNE","family":"KIM","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Department of Information and Communication Engineering, Seokyeong University, Seoul 136-704, Korea"}]},{"given":"HANSEOK","family":"KO","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Korea University, Anam-dong Seongbuk-gu, Seoul 136-713, Korea"}]}],"member":"219","published-online":{"date-parts":[[2012,4,30]]},"reference":[{"key":"rf1","volume-title":"Multitarget-Multisensor Tracking: Principles and Techniques","author":"Bar-Shalom Y.","year":"1995"},{"key":"rf2","first-page":"1","volume":"24","author":"Bonaiuto J.","journal-title":"Vid. Imag. Vis. Comput."},{"key":"rf3","unstructured":"V.\u00a0Cantoni, S.\u00a0Levialdi and V.\u00a0Roberto, Artificial Vision: Image Description, Recognition and Communication (Academic Press, 1997)\u00a0pp. 3\u201364."},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1016\/0042-6989(93)90210-N"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1109\/34.730558"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1007\/11428831_18"},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1007\/11559573_104"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1007\/11565123_43"},{"key":"rf9","doi-asserted-by":"publisher","DOI":"10.1109\/83.350809"},{"key":"rf11","doi-asserted-by":"publisher","DOI":"10.1006\/cviu.2000.0870"},{"key":"rf14","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45482-9_15"},{"key":"rf15","doi-asserted-by":"crossref","unstructured":"J. K.\u00a0Tsotsos, The Selective Tuning Model, Visual Attention Mechanisms, eds. V.\u00a0Cantoni, M.\u00a0Marinaro and A.\u00a0Petrosino (Kluwer Academic\/Plenum Publishers, 2003)\u00a0pp. 239\u2013250.","DOI":"10.1007\/978-1-4615-0111-4_22"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001406005058","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T13:01:47Z","timestamp":1565096507000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001406005058"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,9]]},"references-count":12,"journal-issue":{"issue":"06","published-online":{"date-parts":[[2012,4,30]]},"published-print":{"date-parts":[[2006,9]]}},"alternative-id":["10.1142\/S0218001406005058"],"URL":"https:\/\/doi.org\/10.1142\/s0218001406005058","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,9]]}}}