MOT16: A Benchmark for Multi-Object Tracking
This benchmark addresses the need for standardized evaluation in computer vision, specifically for multi-object tracking, but is incremental as it builds on an existing framework.
The paper introduces MOT16, a new release of the MOTChallenge benchmark for multi-object tracking, which provides carefully annotated videos with consistent protocols, a significant increase in labeled boxes, multiple object classes beyond pedestrians, and visibility levels for each object.
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.