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The Detection of Beard Behavior of Taxi Drivers Based on Traffic Surveillance Video

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Biometric Recognition (CCBR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10996))

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Abstract

This paper presents a method for automatic detection of taxi drivers beard behavior. First, Haar-Adaboost algorithm is used to locate the special window area of taxi. Secondly, the image is preprocessed by multi-scale retina enhancement algorithm on image value channel, then face feature points and chin area are extracted from the window area, and the beard pixel is segmented by skin tone and gray threshold method. Finally, The method was tested by real traffic surveillance video and the validity was proved

Z. Wang—Professor-level senior engineer, Computer science and technology.

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References

  1. This newspaper’s commentator: Correctly understanding the relationship between the transportation power and the socialist modernization power (Chinese). China Water Transport, (001), 13 November 2017

    Google Scholar 

  2. Huang, Q.: Current situation and improvement of non-site enforcement (Chinese). J. Shanghai Public Secur. College 17(3), 79–81 (2007)

    Google Scholar 

  3. Cai, X., Gan, K., Yang, C.: The beard detection algorithm based on feature point location and skin color segmentation (Chinese). Video Eng. 40(3), 116–121 (2016)

    Google Scholar 

  4. Gu, Y., Qiu, W.: Beard and hat detection based on CNN (Chinese). Inf. Technol. 9, 121–124 (2017)

    Google Scholar 

  5. Lienhart, R., Maydt, J.: An extended set of Haar-like features for rapid object detection. In: International Conference on Image Processing, Proceedings, vol. 1, pp. I-900–I-903. IEEE (2002)

    Google Scholar 

  6. Viola, P., Jones, M.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004)

    Article  Google Scholar 

  7. Freund, Y., Schapire, R.E.: A desicion-theoretic generalization of on-line learning and an application to boosting. In: Vitányi, P. (ed.) EuroCOLT 1995. LNCS, vol. 904, pp. 23–37. Springer, Heidelberg (1995). https://doi.org/10.1007/3-540-59119-2_166

    Chapter  Google Scholar 

  8. Li, Z., Qiu, H.: Research on fast image matching based on correlation coefficient (Chinese). J. Beijing Inst. Technol. 27(11), 998–1000 (2007)

    Google Scholar 

  9. Jobson, D.J., Rahman, Z.-u., Woodell, G.A.: A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965–976 (1997)

    Article  Google Scholar 

  10. Qin, X., Wang, H., Du, Y.: Retinex structured light image enhancement algorithm in HSV color space (Chinese). J. Comput. Aided Des. Comput. Graph. 25(4), 488–493 (2013)

    Google Scholar 

  11. Li, Y., Lai, J., Ruan, B.: Multi template ASM algorithm and its application in face feature points detection (Chinese). J. Comput. Res. Dev. 44(1), 133–140 (2007)

    Article  Google Scholar 

  12. Liu, C., Zhang, L.: An improved feature point location method for face. J. Fudan Univ. (Nat. Sci.) 45(4), 457–463 (2006)

    MathSciNet  Google Scholar 

Download references

Acknowledgment

This paper is supported by the Project for the National Natural Science Foundation of China under Grants No. 61672064, the Beijing Natural Science Foundation under Grant No. 4172001, the China Postdoctoral Science Foundation under Grants No. 2016T90022, 2015M580029, the Beijing Postdoctoral Science Foundation under Grants No. 2015ZZ-23, the Science and Technology Project of Beijing Municipal Education Commission under Grants No. KZ201610005007, and Beijing Laboratory of Advanced Information Networks under Grants No. 040000546617002, and Beijing Municipal Communications Commission Science and Technology Project under Grants No. 2017058.

Author information

Authors and Affiliations

  1. Traffic Execution BR Gade of Beijing, Beijing, China

    Zuyun Wang

  2. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Xunping Huang, Kebin Jia, Pengyu Liu & Zhonghua Sun

  3. Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China

    Xunping Huang, Kebin Jia, Pengyu Liu & Zhonghua Sun

  4. Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, 100124, China

    Xunping Huang, Kebin Jia, Pengyu Liu & Zhonghua Sun

  5. Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China

    Xunping Huang, Kebin Jia, Pengyu Liu & Zhonghua Sun

Authors
  1. Zuyun Wang
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  2. Xunping Huang
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  3. Kebin Jia
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  4. Pengyu Liu
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  5. Zhonghua Sun
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Corresponding author

Correspondence to Kebin Jia .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Xinjiang University, Urumqi, China

    Zhenhong Jia

  5. Tsinghua University, Beijing, China

    Jianjiang Feng

  6. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  7. Xinjiang University, Urumqi, China

    Kurban Ubul

  8. Tsinghua University, Shenzhen, China

    Zhenhua Guo

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Wang, Z., Huang, X., Jia, K., Liu, P., Sun, Z. (2018). The Detection of Beard Behavior of Taxi Drivers Based on Traffic Surveillance Video. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_69

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  • DOI: https://doi.org/10.1007/978-3-319-97909-0_69

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97908-3

  • Online ISBN: 978-3-319-97909-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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