$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

Feasibility Study of Gait Recognition Using Points in Three-Dimensional Space 원문보기

International journal of fuzzy logic and intelligent systems : IJFIS, v.13 no.2, 2013년, pp.124 - 132  

Kim, Minsung (Department of Transdisciplinary Studies, Seoul National University) ,  Kim, Mingon (Department of Transdisciplinary Studies, Seoul National University) ,  Park, Sumin (Department of Transdisciplinary Studies, Seoul National University) ,  Kwon, Junghoon (Digital Human Research Center, Advanced Institutes of Convergence Technology) ,  Park, Jaeheung (Department of Transdisciplinary Studies, Seoul National University)

Abstract AI-Helper 아이콘AI-Helper

This study investigated the feasibility of gait recognition using points on the body in three-dimensional (3D) space based on comparisons of four different feature vectors. To obtain the point trajectories on the body in 3D, gait motion data were captured from 10 participants using a 3D motion captu...

주제어

AI 본문요약
AI-Helper 아이콘 AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

제안 방법

  • ). All participants walked at their preferred speed under the four different types of shoes (flat shoes of 1.2 cm heel, medium heels of 4.7 cm heel, wedge heels of 7.5 cm heel, and high heels of 9.8 cm heel).
  • The gallery and probe data were used to compare the gait recognition rates with the four different methods. CMC curves were produced to illustrate the performance of the methods. The effect of heel height was also analyzed based on the recognition rates.
  • Gait recognition with the four different shoe conditions was performed using four feature vectors and the recognition rates were compared to determine the characteristics of the feature vectors and the effects of heel height. Finally, the cumulative matching characteristics (CMC) curves were obtained to illustrate the recognition results.
  • In this paper, we proposed four feature vectors for gait recognition based on points on the body in 3D space and we investigated their feasibility by experiments using a 3D motion capture dataset.
  • In this study, we investigated the feasibility of gait recognition based on points on the body in 3D and we also compared four different methods to identify the most effective method for gait recognition using body points. The first two methods used feature vectors extracted from the gait voxel intensity, which is conceptually similar to GEI.

대상 데이터

  • Kinematic data of walking were obtained from 10 participants using Vicon Nexus software. Thirty-five marker point trajectories were extracted in x-axis (anterior direction), y-axis (lateral direction), and z-axis (vertical direction), respectively.
  • Ten women participated in the experiment, whose average age, height and weight were 21.0 ± 0.85 years, 159.68 ± 4.18 cm and 50.10 ± 3.31 kg, respectively.
  • To investigate the effects of heel height on gait recognition from a different viewpoint, the recognition rates in Table 2 were rearranged based on the difference between the heel heights in the gallery and probe data. The experimental shoes are listed by the heel height in ascending order: flat shoes (1.2 cm), medium heels (4.7 cm), wedge heels (7.5 cm), and high heels (9.8 cm).
  • 31 kg, respectively. Thirty-five reflective markers (14 mm spheres) were attached on the body of the participants based on Vicon Plug-in-Gait marker set (4 in the head, 15 in the upper body, and 16 in the lower body). Three walking trials of each participant were captured at 100 Hz by 12 cameras which have a resolution of 16 megapixels (Vicon T160 Camera, Vicon Motion Capture System Ltd.
본문요약 정보가 도움이 되었나요?

참고문헌 (17)

  1. L. Wang, T. Tan, H. Ning, and W. Hu, "Silhouette analysisbased gait recognition for human identification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1505-1518, Dec. 2003. http://dx.doi.org/10.1109/TPAMI.2003.1251144 

  2. A. Kale, A. Sundaresan, A. N. Rajagopalan, N. P. Cuntoor, A. K. Roy-Chowdhury, V. Kruger, and R. Chellappa, "Identification of humans using gait," IEEE Transactions on Image Processing, vol. 13, no. 9, pp. 1163-1173, Sep. 2004. http://dx.doi.org/10.1109/TIP.2004.832865 

  3. J. Han and B. Bhanu, "Individual recognition using gait energy image," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 2, pp. 316-322, Feb. 2006. http://dx.doi.org/10.1109/TPAMI.2006.38 

  4. B. Y. Lee, S. J. Hong, H. S. Lee, and E. T. Kim, "Gaitbased human identification system using eigenfeature regularization and extraction," Journal of Korean Institute of Intelligent Systems, vol. 21, no. 1, pp. 6-11, Feb. 2011. http://dx.doi.org/10.5391/JKIIS.2011.21.1.6 

  5. I. Bouchrika, M. Goffredo, J. N. Carter, and M. S. Nixon, "Covariate analysis for view-point independent gait recognition," in Proceedings of the 3rd International Conference on Advances in Biometrics, Alghero, 2009. pp. 990-999. http://dx.doi.org/10.1007/978-3-642-01793-3_100 

  6. C. BenAbdelkader, R. G. Cutler, and L. S. Davis, "Gait recognition using image self-similarity," EURASIP Journal on Applied Signal Processing, vol. 2004, pp. 572-585, Jan. 2004. http://dx.doi.org/10.1155/S1110865704309236 

  7. L. Wang, T. Tan, W. Hu, and H. Ning, "Automatic gait recognition based on statistical shape analysis," IEEE Transactions on Image Processing, vol. 12, no. 9, pp. 1120-1131, Sep. 2003. http://dx.doi.org/10.1109/TIP.2003.815251 

  8. J. Han, B. Bhanu, and A. K. Roy-Chowdhury, "A study on view-insensitive gait recognition," in Proceedings of IEEE International Conference on Image Processing, Genoa, 2005, pp. 297-300. http://dx.doi.org/10.1109/ICIP.2005.1530387 

  9. Y. Pratheepan, J. V. Condell, and G. Prasad, "Individual identification using gait sequences under different covariate factors," in Proceedings of the 7th International Conference on Computer Vision Systems, Liege, 2009, pp. 84-93. http://dx.doi.org/10.1007/978-3-642-04667-4_9 

  10. S. Sivapalan, D. Chen, S. Denman, S. Sridharan, and C. Fookes, "Gait energy volumes and frontal gait recognition using depth images," in Proceedings of International Joint Conference on Biometrics, Washington DC, 2011, pp. 1-6. http://dx.doi.org/10.1109/IJCB.2011.6117504 

  11. G. Zhao, G. Liu, H. Li, and M. Pietikainen, "3D gait recognition using multiple cameras," in Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition, Southampton, 2006, pp. 529-534. http://dx.doi.org/10.1109/FGR.2006.2 

  12. H. Lee, S. Hong, and E. Kim, "An efficient gait recognition with backpack removal," EURASIP Journal on Advances in Signal Processing, vol. 2009, Oct. 2009. http://dx.doi.org/10.1155/2009/384384 

  13. P. J. Phillips, S. Sarkar, I. Robledo, P. Grother, and K. Bowyer, "Baseline results for the challenge problem of HumanID using gait analysis," in Proceedings of 5th IEEE International Conference on Automatic Face and Gesture Recognition, Washington DC, 2002, pp. 130-135. http://dx.doi.org/10.1109/AFGR.2002.1004145 

  14. R. T. Collins, R. Gross, and J. Shi, "Silhouette-based human identification from body shape and gait," in Proceedings of the 5th International Conference on Automatic Face and Gesture Recognition, Washington DC, 2002, pp. 366-371. http://dx.doi.org/10.1109/AFGR.2002.1004181 

  15. G. V. Narasimhulu and S. A. K. Jilani, "Gait recognition: a survey," International Journal of Electronics Communication and Computer Engineering, vol. 3, no. 1, pp. 33-40, 2012. 

  16. I. T. Jolliffe, Principal Component Analysis. 2nd ed., New York: Springer, 2002. 

  17. E. E. Cowley, T. L. Chevalier, and N. Chockalingam, "The effect of heel height on gait and posture: a review of the literature," Journal of the American Podiatric Medical Association, vol. 99, no. 6, pp. 512-518, Nov. 2009. 

저자의 다른 논문 :

관련 콘텐츠

오픈액세스(OA) 유형

GOLD

오픈액세스 학술지에 출판된 논문

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로