• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Wang Ziye, Miao Duoqian, Zhao Cairong, Luo Sheng, Wei Zhihua. A Pedestrian Tracking Algorithm Based on Multi-Granularity Feature[J]. Journal of Computer Research and Development, 2020, 57(5): 996-1002. DOI: 10.7544/issn1000-1239.2020.20190280
Citation: Wang Ziye, Miao Duoqian, Zhao Cairong, Luo Sheng, Wei Zhihua. A Pedestrian Tracking Algorithm Based on Multi-Granularity Feature[J]. Journal of Computer Research and Development, 2020, 57(5): 996-1002. DOI: 10.7544/issn1000-1239.2020.20190280

A Pedestrian Tracking Algorithm Based on Multi-Granularity Feature

Funds: This work was supported by the National Key Research and Development Program of China (213) and the National Natural Science Foundation of China (61976158, 61673301).
More Information
  • Published Date: April 30, 2020
  • Recently in some popular applications, such as video scene surveillance, long-term effective pedestrian tracking is the basis of these applications. Although the related technology of target detection and target tracking have a long history, how to achieve real-time and accurate pedestrian tracking is still an active research field and needs to be solved. At present, most pedestrian tracking methods only use hand-designed features to track or only use deep learning to extract features, which are not good ways to represent the features of the target because the use of one single feature will restrict the expression of the features. Therefore, multi-granularity hierarchical features are used in this paper to achieve more stable pedestrian tracking. This paper proposes an improved pedestrian tracking algorithm. The algorithm adopts the idea of multi-granularity, combines convolutional feature with bottom color feature, makes decision on the tracking result obtained by GOTURN, a tracking algorithm based on deep learning, and modifies the tracking result with target detection. This paper uses Pascal VOC data set for model training, and uses OTB-100 and VOT 2015 data sets for testing. The experimental results show that the tracking algorithm based on multi-granularity decision can track target pedestrians more accurately than a single tracking algorithm and the tracking accuracy is improved obviously.
  • Related Articles

    [1]Zhang Lu, Cao Feng, Liang Xinyan, Qian Yuhua. Cross-Modal Retrieval with Correlation Feature Propagation[J]. Journal of Computer Research and Development, 2022, 59(9): 1993-2002. DOI: 10.7544/issn1000-1239.20210475
    [2]Yan Mingyu, Li Han, Deng Lei, Hu Xing, Ye Xiaochun, Zhang Zhimin, Fan Dongrui, Xie Yuan. A Survey on Graph Processing Accelerators[J]. Journal of Computer Research and Development, 2021, 58(4): 862-887. DOI: 10.7544/issn1000-1239.2021.20200110
    [3]Zhang Yixuan, Guo Bin, Liu Jiaqi, Ouyang Yi, Yu Zhiwen. app Popularity Prediction with Multi-Level Attention Networks[J]. Journal of Computer Research and Development, 2020, 57(5): 984-995. DOI: 10.7544/issn1000-1239.2020.20190672
    [4]Hai Mo, Zhu Jianming. A Propagation Mechanism Combining an Optimal Propagation Path and Incentive in Blockchain Networks[J]. Journal of Computer Research and Development, 2019, 56(6): 1205-1218. DOI: 10.7544/issn1000-1239.2019.20180419
    [5]Li Qin, Zhu Yanchao, Liu Yi, Qian Depei. Accelerator Support in YARN Cluster[J]. Journal of Computer Research and Development, 2016, 53(6): 1263-1270. DOI: 10.7544/issn1000-1239.2016.20148351
    [6]LiFeng, PanJingkui. Human Motion Recognition Based on Triaxial Accelerometer[J]. Journal of Computer Research and Development, 2016, 53(3): 621-631. DOI: 10.7544/issn1000-1239.2016.20148159
    [7]Zhu Xiang, Jia Yan, Nie Yuanping, Qu Ming. Event Propagation Analysis on Microblog[J]. Journal of Computer Research and Development, 2015, 52(2): 437-444. DOI: 10.7544/issn1000-1239.2015.20140187
    [8]Wang Yuewu, Jing Jiwu, Xiang Ji, and Liu Qi. Contagion Worm Propagation Simulation and Analysis[J]. Journal of Computer Research and Development, 2008, 45(2): 207-216.
    [9]Li Aiguo, Hong Bingrong, Wang Si, Piao Songhao. Error Propagation Analysis in Software[J]. Journal of Computer Research and Development, 2007, 44(11): 1962-1970.
    [10]Hu Wei and Qin Kaihuai. A New Rendering Technology of GPU-Accelerated Radiosity[J]. Journal of Computer Research and Development, 2005, 42(6): 945-950.
  • Cited by

    Periodical cited type(4)

    1. 刘艳君,牛丽平. 采用改进积分反演法的四旋翼无人机容错控制. 计算机应用与软件. 2022(06): 70-75+95 .
    2. 宋伟中,王行业,王宁. 一种面向无人机区域协同覆盖的感知任务分配方法. 计算机应用与软件. 2021(05): 75-81 .
    3. 马昊鹏,刘由之,李荣军,阎华,杨卫民. 无人机航母系统的构建与应用. 科技创新与应用. 2020(01): 37-40+43 .
    4. 李鹏举,毛鹏军,耿乾,黄传鹏,方骞,张家瑞. 无人机集群技术研究现状与趋势. 航空兵器. 2020(04): 25-32 .

    Other cited types(4)

Catalog

    Article views (1343) PDF downloads (553) Cited by(8)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return