Visual Tracking: An Experimental Survey

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 a difficult problem, therefore, it remains a most active area of research in computer vision. A good tracker should perform...

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Vydáno v:IEEE transactions on pattern analysis and machine intelligence Ročník 36; číslo 7; s. 1442 - 1468
Hlavní autoři: Smeulders, Arnold W. M., Chu, Dung M., Cucchiara, Rita, Calderara, Simone, Dehghan, Afshin, Shah, Mubarak
Médium: Journal Article
Jazyk:angličtina
Vydáno: Los Alamitos, CA IEEE 01.07.2014
IEEE Computer Society
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Applied sciences
Artificial intelligence
Camera surveillance
Computer science; control theory; systems
Computer vision
Educational institutions
Exact sciences and technology
Image processing
Object tracking
Pattern recognition. Digital image processing. Computational geometry
Radar tracking
Robustness
Target tracking
Tracking dataset
Tracking evaluation
Video understanding
Videos
video understanding
image processing
tracking evaluation
computer vision
camera surveillance
Object tracking
tracking dataset
Occlusion
Mobile phone
Computer vision
Target tracking
Tracking
Motion estimation
Image processing
Video signal
Mobility
Clutter
Survival
Statistical test
Luminance
Surveillance
Illumination
Occultation
ISSN:0162-8828, 1939-3539, 2160-9292, 1939-3539
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Popis
Shrnutí: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 a 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.
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ISSN:0162-8828
1939-3539
2160-9292
1939-3539
DOI:10.1109/TPAMI.2013.230