Journal ArticleDOI
A Metric for Performance Evaluation of Multi-Target Tracking Algorithms
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TLDR
A mathematically rigorous metric is proposed for performance evaluation of multi-target tracking algorithms that is defined on the space of finite sets of tracks and incorporates the labeling error.Abstract:
Performance evaluation of multi-target tracking algorithms is of great practical importance in the design, parameter optimization and comparison of tracking systems. The goal of performance evaluation is to measure the distance between two sets of tracks: the ground truth tracks and the set of estimated tracks. This paper proposes a mathematically rigorous metric for this purpose. The basis of the proposed distance measure is the recently formulated consistent metric for performance evaluation of multi-target filters, referred to as the OSPA metric. Multi-target filters sequentially estimate the number of targets and their position in the state space. The OSPA metric is therefore defined on the space of finite sets of vectors. The distinction between filtering and tracking is that tracking algorithms output tracks and a track represents a labeled temporal sequence of state estimates, associated with the same target. The metric proposed in this paper is therefore defined on the space of finite sets of tracks and incorporates the labeling error. Numerical examples demonstrate that the proposed metric behaves in a manner consistent with our expectations.read more
Citations
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References
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Design and Analysis of Modern Tracking Systems
Samuel S. Blackman,Robert Populi +1 more
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Journal ArticleDOI
A Consistent Metric for Performance Evaluation of Multi-Object Filters
TL;DR: This paper outlines the inconsistencies of existing metrics in the context of multi- object miss-distances for performance evaluation, and proposes a new mathematically and intuitively consistent metric that addresses the drawbacks of current multi-object performance evaluation metrics.
Proceedings Article
On performance evaluation of multi-object filters
TL;DR: This paper outlines the inconsistencies of existing metrics in the context of multi- object miss-distances for performance evaluation, and proposes a new mathematically and intuitively consistent metric that addresses the drawbacks of current multi-object performance evaluation metrics.