Gait Recognition Algorithm Based on the Trajectory of Tiptoe

Yi Bo Li; Qin Yang

doi:10.4028/www.scientific.net/AMR.255-260.1984

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 255-260Gait Recognition Algorithm Based on the Trajectory...

Gait Recognition Algorithm Based on the Trajectory of Tiptoe

Abstract:

Most researchers focus on the gait characteristics of hip and changed angle of knee joints, gait characteristics of foot is still less attention, also apply wavelet packet to analysis more detailed information of characteristics’ data, and use the support vector machine algorithm to reduce the randomness, it has their unique advantages in the small sample. Summarized the above three points of the paper, the paper proposes a new gait recognition method to extract trajectory of tiptoe, uses wavelet packet to analyze it, then applies SVM for classification and recognition. Tested at the NLPR database of Chinese Academy of Sciences of 45 camera angle, we observed that the recognition rate has significantly increased, we observed that the algorithm is an effective identification method.

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Periodical:

Advanced Materials Research (Volumes 255-260)

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1984-1988

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.255-260.1984

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May 2011

Authors:

Yi Bo Li, Qin Yang

Keywords:

Support Vector Machine (SVM), Tiptoe Characteristics, Wavelet Packet Transform

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References

[1] Cunado D, Nixon M, Carter J. Using gait as a biometric, via phase-weighted magnitude spectra. In: Proc International Conference on Audio and Video-based Biometric Person Authentication. Switzerland: Crans-Montana , 1997, 95-102.

DOI: 10.1007/bfb0015984

Google Scholar

[2] H. Yoo, M. Nixon, CJ Harris. Extracting human gait signatures by body segment properties. In: Proc. of IEEE Southwest Symposium on Image Analysis and Interpretation. 2002 , 35-39.

DOI: 10.1109/iai.2002.999885

Google Scholar

[3] Mowbray SD, Nixon, MS Extraction and recognition of periodically deforming objects continuous, spatio-temporal shape description. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Washington, 2004, 326-338.

DOI: 10.1109/cvpr.2004.1315260

Google Scholar

[4] Little, JEBoyd. Recognizing people by their gait: the shape of motion. Videre Electronic J. Compute Vision, 1998, 1 (2) : 1-32.

Google Scholar

[5] Tian guang jian, Gait feature extraction and recognition technology research, 2005. 12. TP391. 444. 2711007444.

Google Scholar