Feature-based Object Tracking using an Active Camera

능동카메라를 이용한 특징기반의 물체추적

  • 정영기 (호남대학교컴퓨터공학과) ;
  • 호요성 (광주과학기술원정보통신공학과)
  • Published : 2004.06.01

Abstract

In this paper, we proposed a feature-based tracking system that traces moving objects with a pan-tilt camera after separating the global motion of an active camera and the local motion of moving objects. The tracking system traces only the local motion of the comer features in the foreground objects by finding the block motions between two consecutive frames using a block-based motion estimation and eliminating the global motion from the block motions. For the robust estimation of the camera motion using only the background motion, we suggest a dominant motion extraction to classify the background motions from the block motions. We also propose an efficient clustering algorithm based on the attributes of motion trajectories of corner features to remove the motions of noise objects from the separated local motion. The proposed tracking system has demonstrated good performance for several test video sequences.

본 논문에서는 능동카메라 환경에서 카메라의 움직임에 의해 유발되는 광역움직임(global motion)과 이동물체에 의해 발생하는 지역움직임(local motion)을 분리한 후, 카메라 팬틸트를 제어하여 물체를 추적하는 특징기반의 추적 시스템을 제안했다. 제안한 시스템은 블록기반 움직임 계측을 통해 연속한 2 프레임 사이의 이동 움직임을 찾고, 이 움직임에서 카메라의 움직임으로 인한 광역 움직임을 제거함으로써 전경물체의 지역 움직임만을 추적한다. 이때, 배경만의 움직임만으로 카메라 움직임을 강건하게 계측하기 위하여, 블록기반 움직임에서 배경움직임을 분류하기 위한 지배적인 움직임 추출방법을 제시한다. 또한 분리된 지역움직임으로부터 잡음물체의 움직임을 제거하기 위하여 꼭지점 특징의 추적궤적 속성에 따른 군집화 알고리즘을 제안한다. 제안한 추적시스템은 여러가지 실험에서 좋은 결과를 보였다.

Keywords

References

  1. Rouke, 0., Badler, 'Model-based Image Ana- lysis of Human Motion using Constraint Propagation,' IEEE Trans. on PAMI, Vol.3, No.4 PP.522-537, 1980
  2. Johansson, G., 'Visual Perception of Bio1o- gical Motion and a Model for Its Analysis." PercepUon and Psychophysics, Vol.14, pp. 201-211, 1973 https://doi.org/10.3758/BF03212378
  3. Gould, K., Shah., M., 'The Trajectory Phmal Sketch: A Multi-Scale Scheme for Representing Motion Characteristics/' IEEE Conf. of CVPR, pp.79-85, 1989
  4. Murray, D., and Basu, A., 'Motion Tracking with an Active Camera IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 5, pp.449-459, May 1994 https://doi.org/10.1109/34.291452
  5. Smithn, S.M., 'ASSET-2:Rea1-Time Motion Segmentation and Object Tracking,' Defense Research Agency Technical Report- 95SMS2, PP.1-25, 1995
  6. Gennery, D.B., 'Tracking known 3-D objects,' Proceedings of AAAI 2nd. Nat. Conference on Artificial Intelligence, pp.13- 17, 1982
  7. Anderson, C.H., Burt, P.L and van der Wal, G.S., 'Change detection and tracking using pyramid transform techniques,' Proceedings of SPIE Conference on Intelligence Robots and Computer Vision, pp.300-305, 1985
  8. Forstner, W., Gulch, E., 'A Fast Operator for Detection and Precise Location of Disttnct Points, Comers, and Centers of Circular of Features' Proc. of the Intercom- mission Conf. On Fast Processing of Photo grammetric Data, PP.281-305, 1987
  9. Beymer, D., McLauchlan, P., Malick, J., 'A real-time computer vision system for mea- suring traffic parameters,' Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 12, pp. 495-501, 1997
  10. Jung, Y.K., Ho, Y.S., 'Robust Vehicle Detec- tion and Tracking for Traffic Surveillance,' Picture Coding Symposium'99, pp.227-230, 1999
  11. Rao, B.S.Y., Durrant-Whyte, H.F., Sheen, J.A., A Fully Decentralized Multi-Sensor System For Tracking and Surveillance,' The Intemational Journal of Robotics Research, Vol. c, PP.20-44, 1993
  12. McFalane, N., Scholfield, C., 'Segmentation and Tracking of Piglets in Images,' Machine Vision and Application, Vol. 8, PP. 187-193, 1995 https://doi.org/10.1007/BF01215814