IEEE Trans Pattern Anal Mach Intell - Visual Tracking: An Experimental Survey.

Tópicos

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{ assess(1506) score(1403) qualiti(1306) }
{ howev(809) still(633) remain(590) }
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{ can(774) often(719) complex(702) }
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{ search(2224) databas(1162) retriev(909) }
{ case(1353) use(1143) diagnosi(1136) }
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{ analysi(2126) use(1163) compon(1037) }
{ imag(2830) propos(1344) filter(1198) }
{ error(1145) method(1030) estim(1020) }
{ research(1085) discuss(1038) issu(1018) }
{ activ(1138) subject(705) human(624) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ patient(2315) diseas(1263) diabet(1191) }
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{ survey(1388) particip(1329) question(1065) }
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{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

There is a large variety of trackers, which have been proposed in the literature during the last two decades with some mixed success. Object tracking in realistic scenarios is difficult problem, therefore it remains a most active area of research in Computer Vision. A good tracker should perform well in a large number of videos involving illumination changes, occlusion, clutter, camera motion, low contrast, specularities and at least six more aspects. However, the performance of proposed trackers have been evaluated typically on less than ten videos, or on the special purpose datasets. In this paper, we aim to evaluate trackers systematically and experimentally on 315 video fragments covering above aspects. We selected a set of nineteen trackers to include a wide variety of algorithms often cited in literature, supplemented with trackers appearing in 2010 and 2011 for which the code was publicly available. We demonstrate that trackers can be evaluated objectively by survival curves, Kaplan Meier statistics, and Grubs testing. We find that in the evaluation practice the F-score is as effective as the object tracking accuracy (OTA) score. The analysis under a large variety of circumstances provides objective insight into the strengths and weaknesses of trackers.

Resumo Limpo

larg varieti tracker propos literatur last two decad mix success object track realist scenario difficult problem therefor remain activ area research comput vision good tracker perform well larg number video involv illumin chang occlus clutter camera motion low contrast specular least six aspect howev perform propos tracker evalu typic less ten video special purpos dataset paper aim evalu tracker systemat experiment video fragment cover aspect select set nineteen tracker includ wide varieti algorithm often cite literatur supplement tracker appear code public avail demonstr tracker can evalu object surviv curv kaplan meier statist grub test find evalu practic fscore effect object track accuraci ota score analysi larg varieti circumst provid object insight strength weak tracker

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