메뉴 건너뛰기




Volumn 3, Issue , 2009, Pages 269-272

Real-time pedestrian detection based on improved gaussian mixture model

Author keywords

Background subtraction; Gaussian mixture model; ITS; Pedestrian detection

Indexed keywords

BACKGROUND IMAGE; BACKGROUND SUBTRACTION; FOREGROUND SEGMENTATION; GAUSSIAN MIXTURE MODEL; GRAPH SEGMENTATION; HOT RESEARCH TOPICS; IMAGE PROCESSING TECHNOLOGY; INTELLIGENT TRANSPORTATION SYSTEMS; ITS; NOVEL COMPONENT; PEDESTRIAN DETECTION; TIME ADJUSTMENT;

EID: 70449372723     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMTMA.2009.93     Document Type: Conference Paper
Times cited : (6)

References (8)
  • 2
    • 0032296592 scopus 로고    scopus 로고
    • W. E. L. Grimson, C. Stauffer, R. Romano, and L. Lee. Using Adaptive Tracking to Classify and Monitor Activities in a Site. Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Santa Barbara, CA, 1998, pp. 22-29.
    • W. E. L. Grimson, C. Stauffer, R. Romano, and L. Lee. Using Adaptive Tracking to Classify and Monitor Activities in a Site. Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Santa Barbara, CA, 1998, pp. 22-29.
  • 3
    • 0032634283 scopus 로고    scopus 로고
    • C. Stauffer, and W. E. L. Grimson. Adaptive Background Mixture Models for Real-time Tracking. Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Fort Collins, CO, 1999, pp. 246-252.
    • C. Stauffer, and W. E. L. Grimson. Adaptive Background Mixture Models for Real-time Tracking. Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Fort Collins, CO, 1999, pp. 246-252.
  • 6
    • 0344741562 scopus 로고    scopus 로고
    • D. S. Lee, J. J. Hull, and B. Erol. A Bayesian framework for Gaussian Mixture Background modeling. Proc. International Conference on Image Processing, 2003, pp. 973-976.
    • D. S. Lee, J. J. Hull, and B. Erol. A Bayesian framework for Gaussian Mixture Background modeling. Proc. International Conference on Image Processing, 2003, pp. 973-976.
  • 7
    • 33847294710 scopus 로고    scopus 로고
    • Y. C. Zhang, Z. Z. Liang, Z. G Hou, H. M. Wang, and M. Tan. An Adaptive Mixture Gaussian Background Model with Online Background Reconstruction and Adjustable Foreground Mergence Time for Motion Segmentation. Proc. IEEE International Conference on Industrial Technology, 2005, pp. 23-27.
    • Y. C. Zhang, Z. Z. Liang, Z. G Hou, H. M. Wang, and M. Tan. An Adaptive Mixture Gaussian Background Model with Online Background Reconstruction and Adjustable Foreground Mergence Time for Motion Segmentation. Proc. IEEE International Conference on Industrial Technology, 2005, pp. 23-27.
  • 8
    • 85139271408 scopus 로고    scopus 로고
    • K. Toyama, J. Krumm, B. Brumitt, and B. Meryers. Wallflower: Principles and Practice of Background Maintenance. Proc. International Conference on Computer Vision, Kerkyra, Greece, 1999, pp. 255-261.
    • K. Toyama, J. Krumm, B. Brumitt, and B. Meryers. Wallflower: Principles and Practice of Background Maintenance. Proc. International Conference on Computer Vision, Kerkyra, Greece, 1999, pp. 255-261.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.