Title
Autonomous Virtual Agents for Performance Evaluation of Tracking Algorithms
Abstract
This paper describes a framework which exploits the use of computer animation to evaluate the performance of tracking algorithms. This can be achieved in two different, complementary strategies. On the one hand, augmented reality allows to gradually increasing the scene complexity by adding virtual agents into a real image sequence. On the other hand, the simulation of virtual environments involving autonomous agents provides with synthetic image sequences. These are used to evaluate several difficult tracking problems which are under research nowadays, such as performance processing long---time runs and the evaluation of sequences containing crowds of people and numerous occlusions. Finally, a general event---based evaluation metric is defined to measure whether the agents and actions in the scene given by the ground truth were correctly tracked by comparing two event lists. This metric is suitable to evaluate different tracking approaches where the underlying algorithm may be completely different.
Year
DOI
Venue
2008
10.1007/978-3-540-70517-8_29
AMDO
Keywords
Field
DocType
virtual agent,event list,autonomous virtual agents,scene complexity,performance evaluation,difficult tracking problem,general event,performance processing,tracking algorithms,different tracking,synthetic image sequence,real image sequence,evaluation metric,ground truth,virtual environment,augmented reality,computer animation
Crowds,Computer vision,Autonomous agent,Computer science,Algorithm,Exploit,Augmented reality,Ground truth,Artificial intelligence,Real image,Computer animation
Conference
Volume
ISSN
Citations 
5098
0302-9743
2
PageRank 
References 
Authors
0.42
7
3
Name
Order
Citations
PageRank
Pau Baiget1443.93
Xavier Roca21087.53
Jordi Gonzalez361748.02