Accelerating Template Matching for Efficient Object Tracking

被引：0
作者：
Cardoso, Alexandre de V. [1 ]
Nedjah, Nadia [1 ]
Mourelle, Luiza de Macedo [2 ]
机构：
[1] Univ Estado Rio De Janeiro, Dept Elect Engn & Telecom, Rio De Janeiro, Brazil
[2] Univ Estado Rio De Janeiro, Dept Syst Engn & Computat, Rio De Janeiro, Brazil
来源：
2019 IEEE 10TH LATIN AMERICAN SYMPOSIUM ON CIRCUITS & SYSTEMS (LASCAS) | 2019年
关键词：
Embedded system; co-design; co-processor; bacteria foraging optimization; template matching; correlation; object tracking;
D O I：
10.1109/lascas.2019.8667596
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Template matching is used to determine the degree of similarity between two images of the same size. Pearson's Correlation Coefficient is applied, due to its property of invariance to brightness changes. This coefficient is computed for each image pixel, entailing a computationally intensive task. In order to accelerate this process, a dedicated co-processor was designed to implement this computation. To improve the search for the maximum correlation point between the image and the template, we used, in this work, Bacteria Foraging Optimization, one of the swarm intelligence strategies. The search process is run by an embedded general purpose processor. The work presented in this paper describes the implementation of the embedded system and compares the results obtained here to those previously obtained when using other swarm intelligent strategies.
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收藏
页码：141 / 144
页数：4
相关论文
共 17 条
  • [1] [Anonymous], SVDK HARDW US GUID R
  • [2] [Anonymous], 2013, Int. J. Adv. Res. Comput. Commun. Eng. (IEEE J.)
  • [3] Benfold B., 2011, 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), P3457, DOI 10.1109/CVPR.2011.5995667
  • [4] Cardoso Alexandre de V., 2018, 9 LAT AM S CIRC SYST, P1, DOI DOI 10.1109/LASCAS.2018.8399903
  • [5] Cardoso Alexandre de V., 2018, P 7 INT C MET NAT IN, P1
  • [6] Cardoso Alexandre V. de, 2018, INT J SWARM INTELLIG, V9, P58
  • [7] Cheng JH, 2012, PROCEEDINGS OF 2012 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2012), P2045, DOI 10.1109/ICCSNT.2012.6526321
  • [8] UAV guidance using a monocular-vision sensor for aerial target tracking
    Choi, Hyunjin
    Kim, Youdan
    [J]. CONTROL ENGINEERING PRACTICE, 2014, 22 : 10 - 19
  • [9] Collins R., 2005, IEEE Int. Workshop Perform Eval. Track. Surveill, V2, P35
  • [10] Mahalakshmi T., 2012, RES J APPL SCI ENG T, V4, P5469
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