Name
Abstract | ||
|---|---|---|
Pedestrian detection and tracking play a significant role in surveillance. Despite the numerous detection and tracking methods proposed in the literature, when the pedestrian is too small to recognize, which is a common case in modern surveillance systems, all methods fail. In order to deal with such case, we propose an active pedestrian tracking system inspired by the human visual system. A coarse-to-fine pedestrian detection algorithm is proposed for the small pedestrian detection by combining the Gaussian mixture model background subtraction with the histogram of oriented gradient detection.
In addition, a three-dimensional pan–tilt–zoom control model is presented, which requires no calibration and is more accurate than other control models. In order to actively track a pedestrian in real time, we utilize an active control algorithm and a tracking–learning–detection tracker. Experimental results demonstrate that our active tracking system is both efficient and effective. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s12559-015-9334-z | Cognitive Computation |
Keywords | Field | DocType |
Active tracking,Pedestrian detection,Coarse-to-fine pedestrian detection,PTZ control model,Human visual system | Background subtraction,Computer vision,Histogram,Pedestrian,Computer science,Human visual system model,Tracking system,Artificial intelligence,Active control,Pedestrian detection,Mixture model | Journal |
Volume | Issue | ISSN |
8 | 1 | 1866-9956 |
Citations | PageRank | References |
5 | 0.44 | 38 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxia Wang | 1 | 16 | 2.60 |
| Qingjie Zhao | 2 | 60 | 2.69 |
| Bo Wang | 3 | 5 | 0.77 |
| shixian wang | 4 | 5 | 0.44 |
| yu zhang | 5 | 5 | 0.44 |
| Wei Guo | 6 | 442 | 146.38 |
| Zhiquan Feng | 7 | 36 | 13.73 |