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| Content Provider | IET Digital Library |
|---|---|
| Author | Zhu, Suguo Du, Junping Ren, Nan |
| Abstract | Deep network has been proven efficient and robust to capture object features in some conditions. It still remains in the stage of classifying or detecting objects. In the field of visual tracking, deep network has not been applied widely. One of the reasons is that its time consuming made the strong method could not meet the speed need of visual tracking. A novel simple tracker is proposed to complete tracking task. A simple six-layer feed-forward backpropagation neural network is applied to capture object features. Nevertheless, this representation is not robust enough when illumination changes or drastic scale changes in dynamic condition. To improve the performance and not to increase much time spent, image perceptual hashing method is employed, which extracts low frequency information of object as its fingerprint to recognize the object from its structure. 64-bit characters are calculated by it, and they are utilized to be the bias terms of the neutral network. This leads more significant improvement for performance of extracting sufficient object features. Then we take particle filter to complete the tracking process with the proposed representation. The experimental results demonstrate that the proposed algorithm is efficient and robust compared with the state-of-the-art tracking methods. |
| Starting Page | 1073 |
| Ending Page | 1078 |
| Page Count | 6 |
| ISSN | 10224653 |
| Volume Number | 26 |
| e-ISSN | 20755597 |
| Issue Number | Issue 5, Sep (2017) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/cje/26/5 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/cje.2016.06.026 |
| Journal | Chinese Journal of Electronics |
| Publisher Date | 2017-09-01 |
| Access Restriction | Open |
| Rights Holder | © Chinese Institute of Electronics |
| Subject Keyword | Backpropagation Computer Vision And Image Processing Technique Deep Learning Deep Network Image Perceptual Hashing Knowledge Engineering Technique Learning in AI Neural Computing Technique Neural Nets Object Classification Object Detection Object Feature Optical, Image And Video Signal Processing Six-layer Feed-forward Backpropagation Neural Network Visual Perception Visual Tracking Algorithm Word Length 64 Bit |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Electrical and Electronic Engineering |
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