Target tracking based on neural network depth feature and texture fusion
文献类型：会议论文
| 作者 | Cao YZ(曹永战)1; Liu, Meiju1; Yang SK(杨尚奎)3 ; Yang, Guodong2; Chen P(陈鹏)3; Zhu SY(朱树云)3; Ge Z(葛壮)3; Liu YW(刘玉旺)3
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| 出版日期 | 2019 |
| 会议日期 | November 29 - December 1, 2019 |
| 会议地点 | Harbin, China |
| 页码 | 1-6 |
| 英文摘要 | This paper presents a method of target tracking based on convolution neural network and texture feature fusion. The lower layer of the convolutional neural network can extract some spatial structure, shape and other features of the target. High-level level can extract relatively abstract semantic information. In this paper, vgg-m convolutional neural network is adopted to realize tracking by adaptive fusion of the extracted depth features of Conv2 and Conv5 with the texture features extracted by two-dimensional Gabor filtering. In this paper, the experimental analysis of this method is carried out on the OTB2013 data set, and the results show that this method can achieve more accurate positioning of the target and has a strong timeliness. |
| 产权排序 | 2 |
| 会议录 | 2019 5th International Conference on Energy Equipment Science and Engineering
 |
| 会议录出版者 | IOP |
| 会议录出版地 | Bristol, UK |
| 语种 | 英语 |
| ISSN号 | 1755-1307 |
| WOS记录号 | WOS:000562932400019 |
| 源URL | [http://ir.sia.cn/handle/173321/26754]  |
| 专题 | 沈阳自动化研究所_空间自动化技术研究室 |
| 通讯作者 | Liu YW(刘玉旺) |
| 作者单位 | 1.Information and Control Engineering Faculty, Shenyang Jianzhu University, Shenyang, LIAONING 110168, China 2.School of Mechanical Engineering and Automation, Northeastern University 3 Wenhua Street, Shenyang 110819, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Cao YZ,Liu, Meiju,Yang SK,et al. Target tracking based on neural network depth feature and texture fusion[C]. 见:. Harbin, China. November 29 - December 1, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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