Name
Abstract | ||
|---|---|---|
This paper presents an approach to human motion tracking using multiple pre-trained activity models for propagation of particles in Annealed Particle Filtering. Hidden Markov models are trained on dimensionally reduced joint angle data to produce models of activity. Particles are divided between models for propagation by HMM synthesis, before converging on a solution during the annealing process. The approach facilitates multi-view tracking of unknown subjects performing multiple known activities with low particle numbers. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICPR.2008.4761157 | 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 |
Keywords | Field | DocType |
training data,hidden markov models,tracking,data models,motion tracking,hidden markov model,annealing,particle filter | Training set,Computer vision,Data modeling,Computer science,Particle filter,Human motion,Artificial intelligence,Hidden Markov model,Match moving,Particle | Conference |
ISSN | Citations | PageRank |
1051-4651 | 8 | 0.50 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Darby | 1 | 62 | 6.81 |
| Baihua Li | 2 | 176 | 21.71 |
| Nicholas Paul Costen | 3 | 8 | 0.83 |