Robust Traffic Monitoring System by Spatio-Temporal Image Analysis

시공간 영상 분석에 의한 강건한 교통 모니터링 시스템

  • Published : 2004.11.01

Abstract

A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

본 논문에서는 교통 영상에서 실시간 교통 정보를 산출하는 새로운 기법을 소개한다. 각 차선의 검지 영역은 통계적 특징과 형상적 특징을 이용하여 도로, 차량, 그리고 그림자 영역으로 분류한다. 한 프레임에서의 오류는 연속된 프레임에서의 차량 영역의 상관적 특징을 이용하여 시공간 영상에서 교정된다. 국부 검지 영역만을 처리하므로 전용의 병렬 처리기 없이도 초당 30 프레임 이상의 실시간 처리가 가능하며 기상조건, 그림자, 교통량의 변화에도 강건한 성능을 보장할 수 있다.

Keywords

References

  1. 이승환, 'ITS의 기본 개념과 국내.외 추진 동향', 대한전자공학회지, Vol. 28, No. 5, pp. 22-26, 2001
  2. Andrew H.S. Lai and Nelson H.C. Yung, 'Vehicle- Type Identification Through Automated Virtual Loop Assignment and Block-Based Direction-Biased Motion Estimation,' IEEE Transactions on Intelligent Transportation Systems, Vol. 1, No.2, pp. 86-97, 2000 https://doi.org/10.1109/6979.880965
  3. V. Kastrinaki, M. Zerakis and K. Kalaitzakis, 'A Survey of Video Processing Techniques for Traffic Applications,' Image and Vision Computing, Vol. 21, pp. 359-381, 2003 https://doi.org/10.1016/S0262-8856(03)00004-0
  4. O. Masoud, et al., 'The Use of Computer Vision in Monitoring Weaving Sections,' IEEE Transactions on Intelligent Transportation Systems, Vol. 2, No. 1, pp.18-25, 2001 https://doi.org/10.1109/6979.911082
  5. S. Gupte, et al., 'Detection and Classification of Vehicles,' IEEE Transactions on Intelligent Transportation Systems, Vol. 3, No. 1, pp. 37-47, 2002 https://doi.org/10.1109/6979.994794
  6. D. Koller, et al., 'Robust Multiple Car Tracking with Occlusion Reasoning,' Proceedings of 3rd European Conference on Computer Vision, Vol. 1, pp. 189-196, 1994
  7. Y. Jung and Y. Ho, 'Traffic Parameter Extraction using Video-based Vehicle Tracking,' Proceedings of IEEE International Conference on ITS, pp. 764-766, 1999 https://doi.org/10.1109/ITSC.1999.821157
  8. R. Cucchiara, M. Piccardi, and P. Mello, 'Image Analysis and Rule-Based Reasoning for a Traffic Monitoring System,' IEEE Transactions on Intelligent Transportation Systems, Vol. 1, No. 2, pp. 119-130, 2000 https://doi.org/10.1109/6979.880969
  9. L.D. Stefano and E. Viarani, 'Vehicle Detection and Tracking Using the Block Matching Algorithm,' Proceeding of 3rd IMACE/lEEE, Vol. 1, pp. 4491-4496, 1999
  10. P.G. Michalopoulos, 'Vehicle detection video through image processing: The Autoscope system,' IEEE Trans. on Vehicular Technology, vol.40, no.1, pp.21-29, 1991 https://doi.org/10.1109/25.69968
  11. 이영재, 이대호, 박영태, '시공간 영상 분석에 의한 실시간 교통 정보 산출 기법', 전자공학회논문지 SP편, 27권, 4호, pp. 11-19, 2000
  12. 이대호, 박영태, '영역 분류와 시공간 영상 분석에 의한 실시간 교통 정보 파라메터 산출 기법', 제12회 영상 처리 및 이해에 관한 워크샵 발표 논문집, pp. 347-352, 2000
  13. L. Wixson, K. Hanna, and D. Mishra, 'Illumination Assessment for Vision-Based Traffic Monitoring,' 1998 IEEE Workshop on Visual Surveillance, pp. 34-41, 1998
  14. 이대호, 박영태, '국부 다중 영역 정보를 이용한 교통 영상에서의 실시간 차량 검지 기법', 2000년도 전자공학회 하계 종합 학술대회 논문집, pp. 163-166, 2000
  15. Z. Zhu, et al., 'VISATRAM: A Real-Time Vision System for Automatic Traffic Monitoring,' Image and Vision Computing, Vol. 18, No. 10, pp. 781-794, 2000 https://doi.org/10.1016/S0262-8856(99)00046-3
  16. M.Y. Siyal and M. Fathy, 'A Neural-Vision based Approach to Measure Traffic Queue Parameters in Real-Time,' Pattern Recognition Letters, Vol. 20, pp. 761-770, 1999 https://doi.org/10.1016/S0167-8655(99)00040-9
  17. M. Fathy and M.Y. Siyal, 'Measuring Traffic Movements at Junctions using Image Processing Techniques,' Pattern Recognition Letters, Vol. 18, pp. 493-500, 1997 https://doi.org/10.1016/S0167-8655(97)00026-3
  18. M. Betke, E. Haritaoglu and L.S. Davis, 'Real-Time Multiple Vehicle Detection and Tracking from Moving Vehicle,' Machine Vision and Application, Vol. 12, pp, 69-83, 2000 https://doi.org/10.1007/s001380050126
  19. S.M. Smith, 'ASSET-2: Real-Time Motion Segmentation and Object Tracking,' Real Time Imaging, Vol. 4, pp. 21-40, 1998 https://doi.org/10.1006/rtim.1996.0061
  20. Z. Duric, et aI., 'Estimating relative Vehicle Motions in Traffic Scenes,' Pattern Recognition, Vol. 35, pp. 1339-1353, 2002 https://doi.org/10.1016/S0031-3203(01)00119-4