computer-vision-19
Online Multi-Object Tracking
3260 papers • 126 benchmarks • 313 datasets
The goal of Online Multi-Object Tracking is to estimate the spatio-temporal trajectories of multiple objects in an online video stream (i.e., the video is provided frame-by-frame), which is a fundamental problem for numerous real-time applications, such as video surveillance, autonomous driving, and robot navigation. Source: A Hybrid Data Association Framework for Robust Online Multi-Object Tracking
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Benchmarks
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MOT16
MOT16
MOT17
MOT17
2D MOT 2015
2D MOT 2015
Libraries
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