Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Gait Recognition Using Multiple Feature detection

다중 특징점 검출을 이용한 보행인식

  • Cho, Woon (Dept. Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University) ;
  • Kim, Dong-Hyeon (Dept. Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University) ;
  • Paik, Joon-Ki (Dept. Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University)
  • 조운 (중앙대학교 첨단영상대학원) ;
  • 김동현 (중앙대학교 첨단영상대학원) ;
  • 백준기 (중앙대학교 첨단영상대학원)
  • Published : 2007.11.25
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Abstract

The gait recognition is presented for human identification from a sequence of noisy silhouettes segmented from video by capturing at a distance. The proposed gait recognition algorithm gives better performance than the baseline algorithm because of segmentation of the object by using multiple modules; i) motion detection, ii) object region detection, iii) head detection, and iv) active shape models, which solve the baseline algorithm#s problems to make background, to remove shadow, and to be better recognition rates. For the experiment, we used the HumanID Gait Challenge data set, which is the largest gait benchmarking data set with 122 objects, For realistic simulation we use various values for the following parameters; i) viewpoint, ii) shoe, iii) surface, iv) carrying condition, and v) time.

본 연구는 원거리에서 걸음걸이 (보행)의 특성을 분석하여 인간을 식별하는 보행인식 (gait recognition) 기술을 다중 특징점 기반으로 확장하여 인식률 및 오류 내성을 향상시키는 기술을 제안한다. 보다 구체적으로 i)움직임 검출, ii) 객체 영역 검출, iii) 머리 영역 검출, 그리고, iv) 능동 형태 모델을 이용하여 기본 알고리듬 (gait baseline algorithm)의 문제점인 전처리 과정없이 그림자 영향과 낮은 인식률을 개선하였다. 제안된 알고리듬은 HumanID Gait Challenge (HGCD) 데이터집합을 이용한 실험을 통해 환경 변화요인에도 강건한 인간 보행인식이 가능함을 확인할 수 있다.

Keywords

References

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