[1]SUN Haiyu,CHEN Xiuhong,XIAO Hanxiong.A deep object tracker with outline response map[J].CAAI Transactions on Intelligent Systems,2019,14(4):725-732.[doi:10.11992/tis.201807029]
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A deep object tracker with outline response map
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 4
Page number:
725-732
Column:
学术论文—人工智能基础
Public date:
2019-07-02
- Title:
- A deep object tracker with outline response map
- Keywords:
- object tracking; neural network; convolutional features; correlation filter; position response; outline information; noise suppression; rectify; deep learning
- CLC:
- TP391
- DOI:
- 10.11992/tis.201807029
- Abstract:
- When convolutional neural network is used as a template to locate target, noise may be unavoidable in the final location response. To solve this problem, we developed a deep object tracker by combining the convolutional position response with the outline position response. For example, in the current frame, after extracting convolutional features and the outline information from the predicted target in the previous frame, we obtained the corresponding convolutional position response and the outline position response, and the latter was used to rectify the former in controlling the noise generated in the convolutional position response. The favorable results of our deep tracker on the benchmark show that the method of integrating the outline position response into the convolutional position response can greatly improve the precision and accuracy of the tracker.
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Last Update:
2019-08-25