Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics
Karlsruhe Institute of Technology
Abstract
Simultaneous tracking of multiple persons in real-world environments is an active research field and several approaches have been proposed, based on a variety of features and algorithms. Recently, there has been a growing interest in organizing systematic evaluations to compare the various techniques. Unfortunately, the lack of common metrics for measuring the performance of multiple object trackers still makes it hard to compare their results. In this work, we introduce two intuitive and general metrics to allow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy in recognizing object configurations and their ability to consistently…
Citation impact
- FWCI
- 17.39
- Percentile
- 100%
- References
- 13
Authors
2Topics & keywords
- Biometrics
- Computer science
- Artificial intelligence
- Computer vision
- Video tracking
- Object (grammar)
- Pattern recognition (psychology)
- Partnerships for the goals