Multi Object Detection and Tracking from Video File
2014 ◽
Vol 533
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pp. 218-225
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Keyword(s):
This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.
2011 ◽
Vol 130-134
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pp. 3862-3865
2015 ◽
Vol 734
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pp. 203-206
2018 ◽
Vol 155
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pp. 01016
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Keyword(s):
2021 ◽
Vol 11
(1)
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pp. 217
2017 ◽
Vol XLII-2/W4
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pp. 67-71
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2017 ◽
Vol 8
(2)
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pp. 287
2013 ◽
Vol 718-720
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pp. 2318-2323