Now you see me: evaluating performance in long-term visual tracking

04/19/2018
by   Alan Lukežič, et al.
2

We propose a new long-term tracking performance evaluation methodology and present a new challenging dataset of carefully selected sequences with many target disappearances. We perform an extensive evaluation of six long-term and nine short-term state-of-the-art trackers, using new performance measures, suitable for evaluating long-term tracking - tracking precision, recall and F-score. The evaluation shows that a good model update strategy and the capability of image-wide re-detection are critical for long-term tracking performance. We integrated the methodology in the VOT toolkit to automate experimental analysis and benchmarking and to facilitate the development of long-term trackers.

READ FULL TEXT

page 7

page 9

page 12

page 13

research
06/19/2019

Performance Evaluation Methodology for Long-Term Visual Object Tracking

A long-term visual object tracking performance evaluation methodology an...
research
04/11/2022

MONCE Tracking Metrics: a comprehensive quantitative performance evaluation methodology for object tracking

Evaluating tracking model performance is a complicated task, particularl...
research
10/27/2019

Exploring 3 R's of Long-term Tracking: Re-detection, Recovery and Reliability

Recent works have proposed several long term tracking benchmarks and hig...
research
04/11/2018

Long-term Compliance Habits: What Early Data Tells Us

The rise in popularity of physical activity trackers provides extensive ...
research
08/02/2023

Learning Spatial Distribution of Long-Term Trackers Scores

Long-Term tracking is a hot topic in Computer Vision. In this context, c...
research
07/28/2021

Rank-based verification for long-term face tracking in crowded scenes

Most current multi-object trackers focus on short-term tracking, and are...
research
06/29/2017

Robust Face Tracking using Multiple Appearance Models and Graph Relational Learning

This paper addresses the problem of appearance matching across different...

Please sign up or login with your details

Forgot password? Click here to reset