한국정보과학회논문지:소프트웨어및응용 (Journal of KIISE:Software and Applications)

한국정보과학회 (Korean Institute of Information Scientists and Engineers)
권호 표지

조명변화와 곁침에 강건한 적응적 모델 기반 다중객체 추적

Adaptive Model-based Multi-object Tracking Robust to Illumination Changes and Overlapping

  • 이경미 (덕성여자대학교 컴퓨터과학부) ;
  • 이윤미 (덕성여자대학교 전산및정보통신대학원)
  • 발행 : 2005.05.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 고정된 카메라로부터 획득된 색상 비디오 프레임에서 조명변화와 겹침으로 인한 왜곡에 강건하게 다수의 사람을 추적하는 방법을 제안한다. 조명변화에 따른 외형변화의 문제점을 해결하기 위하여 시간 비종속적인 본래(intrinsic) 영상을 이용하여 프레임에 존재하는 조명을 제거하며, 매 프레임마다 조명 영상을 적응적으로 갱신한다. 카메라 내에서 사람을 추적하기 위해 색상정보를 포함하는 계충적 사람모델을 사용함으로써 겹침의 문제를 해결한다. 추적된 사람모델은 사람모델 리스트에 저장되어 해당되는 사람이 카메라에서 사라진 후에도 일정 기간 보존됨으로써, 재등장한 사람의 정보를 복원할 수 있다. 본 논문에서 제안하는 적응적 모델기반 방법은 실내${\cdot}$외 영상을 대상으로 여러 시나리오로 실험되어, 조명변화로 왜곡된 사람의 색상정보를 옳게 보정하였을 뿐만 아니라 사람들이 겹치거나 헤어진 후에도 성공적으로 추적하였음을 확인하였다.

This paper proposes a method to track persons robustly in illumination changes and partial occlusions in color video frames acquired from a fixed camera. To solve a problem of changing appearance by illumination change, a time-independent intrinsic image is used to remove noises in an frame and is adaptively updated frame-by-frame. We use a hierarchical human model including body color information in order to track persons in occlusion. The tracked human model is recorded into a persons' list for some duration after the corresponding person's exit and is recovered from the list after her reentering. The proposed method was experimented in several indoor and outdoor scenario. This demonstrated the potential effectiveness of an adaptive model-base method that corrected distorted person's color information by lighting changes, and succeeded tracking of persons which was overlapped in a frame.

키워드

참고문헌

  1. C. Wren, A. Azarbayejani, T. Darrell and A. Pentland, 'Pfinder: Real-time tracking of the human body,' IEEE trans. on PAMI, 19(7):780-785, 1997 https://doi.org/10.1109/34.598236
  2. S. Park and J. K. Aggarwa, 'Segmentation and tracking of interacting human body parts under occlusion and shadowing,' in Proc.of Intemntional Workshop on Motion and Video Computing, pp. 105-111, 2002 https://doi.org/10.1109/MOTION.2002.1182221
  3. Y. Ricquebourg and P. Bouthemy, 'Real-time tracking of moving persons by exploiting spatio-temporal image slices,' IEEE trans. on PAMI, 22(8):797-808, 2000 https://doi.org/10.1109/34.868682
  4. Y. Huang and T. S. Huang, 'Model-based human body tracking,' in Proc. of International Conference on Pattem Recognition, pp. 552-555, 2002 https://doi.org/10.1109/ICPR.2002.1044791
  5. M. B. Capellades, D. Doermann, D. DeMenthon and R. Chellappa, 'An appearance based approach for human and object tracking,' in Proc. of International Conference on Image Processing, pp. 85-88, 2003
  6. P. D. O'Malley, M. C. Nechyba and A. A. Arroyo, 'Human activity tracking for wide-area surveillance,' in Proc. of Florida Conference on Recent Advances in Robotics, 2002
  7. O. Javed, Z. Rasheed, O. Alatas and M. Shah, 'KNIGHTM: A real-time surveillance system for multiple overlapping and non-overlapping cameras,' in Proc. of the fourth International Conference on Multimedia and Expo, 2003 https://doi.org/10.1109/ICME.2003.1221001
  8. S. Khan and M. Shah, 'Consistent labeling of tracked objects in multiple cameras with overlapping fields of view,' IEEE trans. on PAMI, 25(10): 1355-1360, 2003 https://doi.org/10.1109/TPAMI.2003.1233912
  9. I. Haritaolu, D. Harwood and L. S. Davis, 'W4: real-time surveillance of people and their activities,' IEEE Trans. on PAMI, 22(8): 809-830, 2000 https://doi.org/10.1109/34.868683
  10. S. J. McKenna, S. Jabri, Z. Durie and H. Wechsler, 'Tracking interacting people,' in Proc. of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition, pp.348-353, 2000 https://doi.org/10.1109/AFGR.2000.840658
  11. J. K. Aggarwal, and Q. Cai, 'Human motion analysis: A review,' Computer vision and image understanding, 73(3):428-440, 1999 https://doi.org/10.1006/cviu.1998.0744
  12. D. Gavrila, 'The visual analysis of human movement: A survey,' Computer vision and image understanding, 73(1):82-98, 1999 https://doi.org/10.1006/cviu.1998.0716
  13. A. Prati, I. Mikic, M. M. Trivedi, and R. Cucchiara, 'Detecting moving shadows: algorithms and evaluation,' IEEE trans. on PAMI, 25(7): 918-923, 2003 https://doi.org/10.1109/TPAMI.2003.1206520
  14. Y. Matsushita, K. Nishino, K. Ikeuchi and M. Sakauchi, 'Illumination normalization with time-dependent intrinsic images for video surveillance,' IEEE trans. on PAMI, 26(10):1336-1347, 2004 https://doi.org/10.1109/TPAMI.2004.86
  15. K. M. Lee, and W. N. Street, 'Model-based detection, segmentation and classification using on-line shape learning,' Machine vision and application, 13(4):222-233, 2003 https://doi.org/10.1007/s00138-002-0061-6
  16. K. M. Lee, and Y. M. Lee, 'Tracking multi-person robust to illumination changes and occlusions,' in Proc. of International of Conference on Artificial reality and Telexistence, pp. 429-432, 2004
  17. C. Garcia and G. Tziritas, 'Face detection using quantized skin color regions merging and wavelet packet analysis,' IEEE Trans. Multimedia, vol. 1, no. 3, pp. 264-277, 1999 https://doi.org/10.1109/6046.784465