Title
A Novel Performance Evaluation Methodology for Single-Target Trackers.
Abstract
This paper addresses the problem of single-target tracker performance evaluation. We consider the performance measures, the dataset and the evaluation system to be the most important components of tracker evaluation and propose requirements for each of them. The requirements are the basis of a new evaluation methodology that aims at a simple and easily interpretable tracker comparison. The ranking-based methodology addresses tracker equivalence in terms of statistical significance and practical differences. A fully-annotated dataset with per-frame annotations with several visual attributes is introduced. The diversity of its visual properties is maximized in a novel way by clustering a large number of videos according to their visual attributes. This makes it the most sophistically constructed and annotated dataset to date. A multi-platform evaluation system allowing easy integration of third-party trackers is presented as well. The proposed evaluation methodology was tested on the VOT2014 challenge on the new dataset and 38 trackers, making it the largest benchmark to date. Most of the tested trackers are indeed state-of-the-art since they outperform the standard baselines, resulting in a highly-challenging benchmark. An exhaustive analysis of the dataset from the perspective of tracking difficulty is carried out. To facilitate tracker comparison a new performance visualization technique is proposed.
Year
DOI
Venue
2015
10.1109/TPAMI.2016.2516982
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keywords
Field
DocType
Visualization,Target tracking,Measurement uncertainty,Performance evaluation,Benchmark testing,Surveillance
Data mining,BitTorrent tracker,Computer vision,Ranking,Visualization,Computer science,Measurement uncertainty,Baseline (configuration management),Equivalence (measure theory),Artificial intelligence,Cluster analysis,Benchmark (computing)
Journal
Volume
Issue
ISSN
abs/1503.01313
11
0162-8828
Citations 
PageRank 
References 
103
2.93
65
Authors
9
Search Limit
100103
Name
Order
Citations
PageRank
Matej Kristan196047.02
Jiri Matas228314.03
Ales Leonardis31636147.33
Tomás Vojír440314.52
Pflugfelder Roman53289.32
Fernandez Gustavo63049.21
Georg Nebehay71877.79
Fatih Porikli83409169.13
Luka Čehovin956018.04