연구동향 분석

온라인 학습을 이용한 비전 기반의 차량 검출 및 추적

길성호(Sung-Ho Gil) 김경환(Gyeong-Hwan Kim) 2014년

논문상세정보
인용/피인용
' 온라인 학습을 이용한 비전 기반의 차량 검출 및 추적' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 전기통신
  • bootstrapping
  • real-time
  • semi-supervised learning
  • vehicle detection
  • vehicle tracking
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
1,698 0

0.0%

' 온라인 학습을 이용한 비전 기반의 차량 검출 및 추적' 의 참고문헌

  • Tracking-learning-detection
    Z. Kalal IEEE Trans. Pattern Analysis and Machine Intelligence 34 (7) [2012]
  • Robust visual tracking and vehicle classification via sparse representation
    X. Mei IEEE Trans. Pattern Analysis and Machine Intelligence 33 (11) : 2259 ~ 2272 [2011]
  • Rapid object detection using a boosted cascade of simple features
    Jones, M. Viola, P. Proc. CVPR Conf. 1 : 511 ~ 518 [2001]
  • Pyramidal implementation of the Lucas Kanade feature tracker description of the algorithm, Technical Report
  • P-N learning: Bootstrapping binary classifiers by structural constraints
    Z. Kalal Proc. CVPR Conf. : 49 ~ 56 [2010]
  • Online boosting for vehicle detection
    W. Chang IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics 40 (3) : 892 ~ 902 [2010]
  • On-road vehicle detection: A review
    Z. Sun IEEE Trans. Pattern Analysis and Machine Intelligence 28 (5) : 694 ~ 711 [2006]
  • Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behavior analysis
    S. Sivaraman IEEE Trans. Intelligent Transportation Systems : 1773 ~ 1795 [2013]
  • Good features to track
    Tomasi, C. Shi, J. Proc. CVPR Conf. : 593 ~ 600 [1994]
  • Fast keypoint recognition in ten lines of code
    M. Ozuysal Proc. CVPR Conf. : 1 ~ 8 [2007]
  • Fast On-Road Vehicle Detection Using Reduced Multivariate Polynomial Classifier
    김중락 한국통신학회논문지 37 (8) : 639 ~ 647 [2012]
  • A system for real-time detection and tracking of vehicles from a single car-mounted camera
    C. Caraffi Proc. ITSC Conf. : 975 ~ 982 [2012]
  • A comparative study of semi-naive bayes methods in classification learning
    F. Zheng Proc. of the Fourth Australasian Data Mining Conference (AusDM05) : 141 ~ 156 [2005]