| Hu Zhentao(胡振涛)*,Mao Yihao*,Fu Chunling**,Liu Xianxing*.[J].高技术通讯(英文),2020,26(4):402~410 |
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| Anti-occlusion pedestrian tracking algorithm based on location prediction and deep feature rematch |
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| DOI：10.3772/j.issn.1006-6748.2020.04.007 |
| 中文关键词: |
| 英文关键词: pedestrian tracking, correlation filter, Kalman filter, deep feature |
| 基金项目: |
| Author Name | Affiliation | | Hu Zhentao(胡振涛)* | (*College of Computer and Information Engineering, Henan University, Kaifeng 475004, P.R.China) | | Mao Yihao* | (*College of Computer and Information Engineering, Henan University, Kaifeng 475004, P.R.China) | | Fu Chunling** | (**School of Physics and Electronics, Henan University, Kaifeng 475004, P.R.China) | | Liu Xianxing* | (*College of Computer and Information Engineering, Henan University, Kaifeng 475004, P.R.China) |
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| 中文摘要: |
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| 英文摘要: |
| Aiming to the problem of pedestrian tracking with frequent or long-term occlusion in complex scenes, an anti-occlusion pedestrian tracking algorithm based on location prediction and deep feature rematch is proposed. Firstly, the occlusion judgment is realized by extracting and utilizing deep feature of pedestrian’s appearance, and then the scale adaptive kernelized correlation filter is introduced to implement pedestrian tracking without occlusion. Secondly, Karman filter is introduced to predict the location of occluded pedestrian position. Finally, the deep feature is used to the rematch of pedestrian in the reappearance process. Simulation experiment and analysis show that the proposed algorithm can effectively detect and rematch pedestrian under the condition of frequent or long-term occlusion. |
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