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Analyzing of Mean-Shift Algorithm in Gray Target Tracking Technology

  • Conference paper
Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7002))

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Abstract

Target tracking technology is an extreme important project in computer vision technology area. Its development can directly force the development of the automatic steer technique. According to target tracking, scientists research out many important tracking algorithms. Mean-shift algorithm is an important computational method in various of target tracking algorithms, which adopts the features of anti-size change, anti-rotation change, and few manual intervention showing the extremely vital role in modern target tracking area. While not all tracking techniques can achieve good effects to it. Therefore, the article analyzed the algorithm from the aspect of practical engineering. And use local difference algorithm to make further improvement to it. Finally through three groups of tracking examples to point out the advantages and disadvantages of this algorithm and the advantages of improved algorithm, and expanded the algorithm using sides.

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References

  1. Fukunaga, K., Hostetler, L.D.: The Estimation of the Gradient of a Density Function with Applications in Pattern Recognition. IEEE Trans. Information Theory 21(5), 32–40 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  2. Comaniciu, D., Meer, P.: Mean Shift: a Robust Approach toward Feature Space Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 603–619 (2002)

    Article  Google Scholar 

  3. Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based Object Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 564–577 (2003)

    Article  Google Scholar 

  4. Kailath, T.: The Divergence and Bhattacharyya Distance Measures in Signal Selection. IEEE Trans. Comm. Technology 15(2), 253–259 (1999)

    Google Scholar 

  5. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal Computer Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. The Engineering & Technical College, Chengdu University of Technology, Leshan, 614000, China

    Shuang Zhang & Gang Jin

  2. The Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, 610209, China

    Shuang Zhang & Yu-Ping Qin

Authors
  1. Shuang Zhang
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  2. Yu-Ping Qin
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  3. Gang Jin
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Zhang, S., Qin, YP., Jin, G. (2011). Analyzing of Mean-Shift Algorithm in Gray Target Tracking Technology. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7002. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23881-9_20

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  • DOI: https://doi.org/10.1007/978-3-642-23881-9_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23880-2

  • Online ISBN: 978-3-642-23881-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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