JOURNAL ARTICLE

Articulated body motion capture by annealed particle filtering

Abstract

The main challenge in articulated body motion tracking is the large number of degrees of freedom (around 30) to be recovered. Search algorithms, either deterministic or stochastic, that search such a space without constraint, fall foul of exponential computational complexity. One approach is to introduce constraints: either labelling using markers or colour coding, prior assumptions about motion trajectories or view restrictions. Another is to relax constraints arising from articulation, and track limbs as if their motions were independent. In contrast, we aim for general tracking without special preparation of objects or restrictive assumptions. The principal contribution of the paper is the development of a modified particle filter for search in high dimensional configuration spaces. It uses a continuation principle based on annealing to introduce the influence of narrow peaks in the fitness function, gradually. The new algorithm, termed annealed particle filtering, is shown to be capable of recovering full articulated body motion efficiently.

Keywords:
Particle filter Computer science Algorithm Computer vision Search algorithm Motion (physics) Tracking (education) Artificial intelligence Simulated annealing Filter (signal processing) Mathematical optimization Mathematics

Metrics

860
Cited By
65.39
FWCI (Field Weighted Citation Impact)
18
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Gait Recognition and Analysis
Physical Sciences →  Engineering →  Biomedical Engineering
Human Pose and Action Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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