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| Content Provider | IET Digital Library |
|---|---|
| Author | Sun, Li Liu, Guizhong Liu, Yiqing |
| Abstract | The authors propose an effective algorithm for multiple pedestrians tracking, which is constructed in the framework of particle filtering, and it is based on the combination of online boosting tracker and the histogram of oriented gradient (HOG) descriptor for human detection. The combination for the detector and tracker lies on following aspects. First, each detection result is associated to a tracker implemented by the online boosting, which gives the authors scheme robustness for multiple similar objects and then, the output of support vector machine classifier based on HOG is dynamically fused as a component in the observation metric in particle filtering, which makes the tracker more accurate in some difficult conditions. Finally, the states of some particles are replaced by the state given by the detector, so that the tracker can recover from failure quickly. Experiments show the effectiveness of their scheme. |
| Starting Page | 653 |
| Ending Page | 659 |
| Page Count | 7 |
| ISSN | 17519659 |
| Volume Number | 7 |
| e-ISSN | 17519667 |
| Issue Number | Issue 7, Oct (2013) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/7/7 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2012.0500 |
| Journal | IET Image Processing |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Computer Vision And Image Processing Technique Filtering Method in Signal Processing Gradient Method Histogram of Gradient Oriented Detections Histogram of Oriented Gradient Descriptor HOG Descriptor HOG Detections Human Detection Interpolation And Function Approximation Knowledge Engineering Technique Multiple Pedestrian Tracking Algorithm Numerical Analysis Object Detection Object Tracking Observation Metric Online Boosting Tracker Optical, Image And Video Signal Processing Particle Filter Particle Flltering Support Vector Machine Support Vector Machine Classifler Video Signal Processing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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