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MOT16: A Benchmark for Multi-Object Tracking | Anton Milan
; Laura Leal-Taixe
; Ian Reid
; Stefan Roth
; Konrad Schindler
; | Date: |
2 Mar 2016 | Abstract: | Standardized benchmarks are crucial for the majority of computer vision
applications. Although leaderboards and ranking tables should not be
over-claimed, benchmarks often provide the most objective measure of
performance and are therefore important guides for reseach.
Recently, a new benchmark for Multiple Object Tracking, MOTChallenge, was
launched with the goal of collecting existing and new data and creating a
framework for the standardized evaluation of multiple object tracking methods.
The first release of the benchmark focuses on multiple people tracking, since
pedestrians are by far the most studied object in the tracking community. This
paper accompanies a new release of the MOTChallenge benchmark. Unlike the
initial release, all videos of MOT16 have been carefully annotated following a
consistent protocol. Moreover, it not only offers a significant increase in the
number of labeled boxes, but also provides multiple object classes beside
pedestrians and the level of visibility for every single object of interest. | Source: | arXiv, 1603.0831 | Services: | Forum | Review | PDF | Favorites |
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