Name
Abstract | ||
|---|---|---|
Pedestrian tracking is an important problem with many practical applications in fields such as security, animation, and human computer interaction (HCI). In this paper, we introduce a previously-unexplored swarm intelligence approach to multi-object monocular tracking by using Bacterial Foraging Optimization (BFO) swarms to drive a novel part-based pedestrian appearance tracker. We show that tracking a pedestrian by segmenting the body into parts outperforms popular blob based methods and that using BFO can improve performance over traditional Particle Swarm Optimization and Particle Filter methods. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CEC.2011.5949658 | IEEE Congress on Evolutionary Computation |
Keywords | Field | DocType |
particle filter methods,particle filtering (numerical methods),part-based pedestrian appearance tracker,human computer interaction,multiobject monocular tracking,bacterial foraging optimization,bacterial foraging optimization swarms,particle swarm optimisation,image segmentation,uncalibrated cameras,pedestrian tracking,object tracking,monocular pedestrian tracking,swarm intelligence approach,swarm intelligence,blob-based methods,indexing terms,particle swarm optimization,histograms,microorganisms,optimization,particle filter | Particle swarm optimization,Histogram,Computer vision,Computer science,Swarm intelligence,Particle filter,Image segmentation,Video tracking,Artificial intelligence,Animation,Foraging | Conference |
ISSN | ISBN | Citations |
Pending | 978-1-4244-7834-7 | 3 |
PageRank | References | Authors |
0.43 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hoang Thanh Nguyen | 1 | 12 | 2.39 |
| Bir Bhanu | 2 | 3356 | 380.19 |