Name
Title | ||
|---|---|---|
Robust multiple object tracking by detection with interacting Markov chain Monte Carlo |
Abstract | ||
|---|---|---|
This paper presents a novel and computationally efficient multi-object tracking-by-detection algorithm with interacting particle filters. The proposed online tracking methodology could be scaled to hundreds of objects and could be completely parallelized. For every object, we have a set of two particle filters, i.e. local and global. The local particle filter models the local motion of the object. The global particle filter models the interaction with the other objects and scene. These particle filters are integrated into a unified Interacting Markov Chain Monte Carlo (IMCMC) framework. The local particle filter improves its performance by interacting with the global particle filter while they both are run in parallel. We indicate the manner in which we bring in object interaction and domain specific information into account by using global filters without further increase in complexity. Most importantly, the complexity of the proposed methodology varies linearly in the number of objects. We validated the proposed algorithms on two completely different domains 1) Pedestrian Tracking in urban scenarios 2) Biological cell tracking (Melanosomes). The proposed algorithm is found to yield favorable results compared to the existing algorithms. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICIP.2013.6738608 | ICIP |
Keywords | Field | DocType |
robust multiple object tracking by detection,pedestrians,particle filtering (numerical methods),interacting particle filters,urban scenarios,interacting markov chain monte carlo,domain specific information,local particle filter,particle filters,online tracking methodology,imcmc framework,biology computing,tracking,biological cell tracking,pedestrian tracking,object tracking,monte carlo methods,object detection,detection,object interaction,melanosomes,markov processes,global particle filter,image motion analysis,object local motion | Object detection,Computer vision,Monte Carlo method,Markov process,Markov chain Monte Carlo,Computer science,Particle filter,Video tracking,Artificial intelligence,Biological cell | Conference |
ISSN | Citations | PageRank |
1522-4880 | 4 | 0.39 |
References | Authors | |
13 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Santhoshkumar Sunderrajan | 1 | 41 | 4.89 |
| S. Karthikeyan | 2 | 148 | 15.16 |
| B. S. Manjunath | 3 | 20 | 1.85 |