Name
Title | ||
|---|---|---|
Continuous Vehicle Detection and Tracking for Non-overlapping Multi-camera Surveillance System. |
Abstract | ||
|---|---|---|
Vehicle detection and tracking has always been a significant research on traffic surveillance video. However, multi-camera object tracking consists of a non-overlapping video surveillance network, which makes vehicle re-identification a challenging problem. In this paper, we proposed a novel method for continuous vehicle detection and tracking in multi-camera campus surveillance videos. The method contains two main parts: One is auto vehicle detection and tracking by using background modeling combining with RCNN (Region Convolutional Neural Networks). The other one is multi-camera vehicle re-identification, which collaborates vehicle visual attributes and spatio-temporal information. The experiment results demonstrate that the proposed approach performs with high efficiency and accuracy, which can also be employed to optimize the trajectories of vehicles in multi-camera surveillance videos. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/3007669.3007705 | ICIMCS |
Keywords | Field | DocType |
Non-overlapping, multi-camera, vehicle detection, vehicle trajectory tracking | Computer vision,Multi camera,Convolutional neural network,Computer science,Tracking system,Vehicle detection,Video tracking,Artificial intelligence,Vehicle tracking system | Conference |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinjia Peng | 1 | 7 | 1.54 |
| Tianyi Shen | 2 | 9 | 1.23 |
| Yafei Wang | 3 | 17 | 4.04 |
| Tongtong Zhao | 4 | 21 | 6.33 |
| Jun Zhang | 5 | 0 | 1.01 |
| Xianping Fu | 6 | 71 | 23.89 |