Data Association and Its Applications to Intelligent Systems: A Review

데이터 연관 문제와 지능시스템에서의 응용: 리뷰

  • 오성희 (서울대학교 전기.정보공학부)
  • Received : 2012.04.03
  • Accepted : 2012.04.12
  • Published : 2012.05.25

Abstract

Data association plays an important role in intelligent systems. This paper presents the Bayesian formulation of data association and its applications to intelligent systems. We first describe the Bayesian formulation of data association developed for solving multi-target tracking problems in a cluttered environment. Then we review applications of data association in intelligent systems, including surveillance using wireless sensor networks, identity management for air traffic control, camera network localization, and multi-sensor fusion.

데이터 연관은 지능시스템의 자율적인 작동에 매우 중요한 문제이다. 본 논문에서는 데이터 연관 문제를 Bayesian 방식으로 구성하고 이를 성공적으로 지능시스템에 응용한 예를 설명한다. 먼저 데이터 연관 문제가 어떻게 Bayesian 방식으로 구성하여 혼잡한 환경에서의 다 물체 추적 문제에 적용되는지 알아본다. 그리고 데이터 연관이 지능시스템에 어떻게 응용될 수 있는지 정체 관리를 이용한 항공 교통 관제, 카메라 네트워크 위치 및 관점 자동 보정, 멀티 센서 퓨젼의 세 가지 예를 이용해 살펴본다.

Keywords

References

  1. D. Reid, An algorithm for tracking multiple targets, IEEE Trans. Automatic Control 24 (6) (1979) 843-854. https://doi.org/10.1109/TAC.1979.1102177
  2. Y. Bar-Shalom, T. Fortmann, Tracking and Data Association, Academic Press, San Diego, CA, 1988.
  3. S. Oh, S. Russell, S. Sastry, Markov chain Monte Carlo data association for multi-target tracking, IEEE Trans. Automatic Control 54 (3) (2009) 481-497. https://doi.org/10.1109/TAC.2009.2012975
  4. I. Cox, A review of statistical data association techniques for motion correspondence, International Journal of Computer Vision 10 (1) (1993) 53-66. https://doi.org/10.1007/BF01440847
  5. I. Cox, S. Hingorani, An efficient implementation of Reid''s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking, IEEE Trans. Pattern Analysis and Machine Intelligence 18 (2) (1996) 138-150. https://doi.org/10.1109/34.481539
  6. D. Forsyth, J. Ponce, Computer Vision: A Modern Approach, Prentice-Hall, 2003.
  7. S. Thrun,W. Burgard, D. Fox, Probabilistic Robotics, Intelligent Robotics and Autonomous Agents, MIT Press, 2005.
  8. U. Frese, A discussion of simultaneous localization and mapping, Autonomous Robots 20 (1) (2006) 25-42. https://doi.org/10.1007/s10514-006-5735-x
  9. S. Oh, L. Schenato, P. Chen, S. Sastry, Tracking and coordination of multiple agents using sensor networks: System design, algorithms and experiments, Proceedings of the IEEE 95 (1) (2007) 234-254. https://doi.org/10.1109/JPROC.2006.887296
  10. H. Pasula, B. Marthi, B. Milch, S. Russell, I. Shpitser, Identity uncertainty and citation matching, in: Advances in Neural Information Processing Systems 15, MIT Press, 2003.
  11. G. Cybenko, V. Berk, V. Crespi, R. Gray, G. Jiang, An overview of process query systems, in: Proc. of SPIE Vol. 5403, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense III, Orlando, FL, 2004.
  12. H. Pasula, S. J. Russell, M. Ostland, Y. Ritov, Tracking many objects with many sensors, in: Proc. of the International Joint Conference on Artificial Intelligence, Stockholm, 1999.
  13. T. Kurien, Issues in the design of practical multitarget tracking algorithms, in: Y. Bar-Shalom (Ed.), Multitarget-Multisensor Tracking: Advanced Applications, Artech House, Norwood, MA, 1990.
  14. A. Poore, Multidimensional assignment and multitarget tracking, in: I. J. Cox, P. Hansen, B. Julesz (Eds.), Partitioning Data Sets, American Mathematical Society, 1995, pp. 169-196.
  15. I. Hwang, K. Roy, H. Balakrishnan, C. Tomlin, A distributed multipletarget identity management algorithm in sensor networks, in: Proc. of the 43rd IEEE Conference on Decision and Control, Bahamas, 2004.
  16. S. Oh, I. Hwang, S. Sastry, Distributed multi-target tracking and identity management, Journal of Guidance, Control, and Dynamics 31 (1) (2008) 12-29. https://doi.org/10.2514/1.26237
  17. I. Hwang, H. Balakrishnan, K. Roy, C. Tomlin, Multiple-target tracking and identity management with application to aircraft tracking, AIAA Journal of Guidance, Control and Dynamics.
  18. P.W.-C. Chen, P. Ahammad, C. Boyer, S.-I. Huang, L. Lin, E. J. Lobaton, M. L. Meingast, S. Oh, S. Wang, P. Yan, A. Yang, C. Yeo, L.-C. Chang, D. Tygar, S. S. Sastry, CITRIC: A low-bandwidth wireless camera network platform, in: Proc. of the ACM/IEEE International Conference on Distributed Smart Cameras, Stanford University, CA, 2008.
  19. M. Meingast, S. Oh, S. Sastry, Automatic camera network localization using object image tracks, in: Proc. of the IEEE International Conference on Computer Vision Workshop on Visual Representations and Modeling of Large-scale environments, Rio de Janeiro, Brazil, 2007.
  20. M. Maroti, B. Kusy, G. Balogh, P. Volgyesi, A. Nadas, K. Molnar, S. Dora, A. Ledeczi, Radio interferometric geolocation, in: Proc. of ACM SenSys, 2005.
  21. M. Meingast, M. Kushwaha, S. Oh, X. Koutsoukos, A. Ledeczi, S. Sastry, Fusion-based localization for a heterogeneous camera network, in: Proc. of the ACM/IEEE International Conference on Distributed Smart Cameras, Stanford University, CA, 2008.
  22. M. Kushwaha, S. Oh, I. Amundson, X. Koutsoukos, A. Ledeczi, Target tracking in heterogeneous sensor networks using audio and video sensor fusion, in: Proc. of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Seoul, Korea, 2008.
  23. J. Chen, L. Yip, J. Elson, H. Wang, D. Maniezzo, R. Hudson, K. Yao, D. Estrin, Coherent acoustic array processing and localization on wireless sensor networks, in: Proceedings of the IEEE, Vol. 91, 2003, pp. 1154-1162.
  24. P. KaewTraKulPong, R. B. Jeremy, An improved adaptive background mixture model for realtime tracking with shadow detection, in: Workshop on Advanced Video Based Surveillance Systems (AVBS), 2001.
  25. S. Karimi-Ashtiani, C. C. J. Kuo, Automatic real-time moving target detection from infrared video, in: International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP''06), 2006.
  26. Y. H. Jung, H, S. Shin, Suboptimal Detection Thresholds for Tracking in Clutter, IEEK, vol. 39-SC, no. 2, pp. 92-97, 2002.