Proceedings ArticleDOI
Evaluating Multi-Object Tracking
Kevin Smith,Daniel Gatica-Perez,Jean-Marc Odobez,Sileye Ba +3 more
- pp 36-36
TLDR
The tracking characteristics important to measure in a real-life application are explored, focusing on configuration and identification, and a set of measures and a protocol to objectively evaluate these characteristics are defined.Abstract:
Multiple object tracking (MOT) is an active and challenging research topic. Many different approaches to the MOT problem exist, yet there is little agreement amongst the community on how to evaluate or compare these methods, and the amount of literature addressing this problem is limited. The goal of this paper is to address this issue by providing a comprehensive approach to the empirical evaluation of tracking performance. To that end, we explore the tracking characteristics important to measure in a real-life application, focusing on configuration (the number and location of objects in a scene) and identification (the consistent labeling of objects over time), and define a set of measures and a protocol to objectively evaluate these characteristics.read more
Citations
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Journal ArticleDOI
Evaluating multiple object tracking performance: the CLEAR MOT metrics
TL;DR: This work introduces 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 label objects over time.
Posted Content
MOT16: A Benchmark for Multi-Object Tracking
TL;DR: A new release of the MOTChallenge benchmark, which focuses on multiple people tracking, and 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.
Proceedings ArticleDOI
Globally-optimal greedy algorithms for tracking a variable number of objects
TL;DR: A near-optimal algorithm based on dynamic programming which runs in time linear in the number of objects andlinear in the sequence length is given which results in state-of-the-art performance.
Posted Content
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking
TL;DR: With MOTChallenge, the work toward a novel multiple object tracking benchmark aimed to address issues of standardization, and the way toward a unified evaluation framework for a more meaningful quantification of multi-target tracking is described.
Journal ArticleDOI
Framework for Performance Evaluation of Face, Text, and Vehicle Detection and Tracking in Video: Data, Metrics, and Protocol
Rangachar Kasturi,Dmitry B. Goldgof,Padmanabhan Soundararajan,Vasant Manohar,J. Garofolo,R. Bowers,Matthew Boonstra,Valentina N. Korzhova,Jing Zhang +8 more
TL;DR: The goal of this work was to systematically address the challenges of object detection and tracking through a common evaluation framework that permits a meaningful objective comparison of techniques, provides the research community with sufficient data for the exploration of automatic modeling techniques, encourages the incorporation of objective evaluation into the development process, and contributes useful lasting resources.
References
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