연구동향 분석

SFMOG : 초고속 MOG 기반 배경 제거 알고리즘

송석빈 김진헌 2019년

논문상세정보
인용/피인용
' SFMOG : 초고속 MOG 기반 배경 제거 알고리즘' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Background Subtraction
  • CVPR 2014 Change Detection benchmark dataset
  • Mixture of gaussian
  • gaussian mixture model
  • image processing
  • real time
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
548 0

0.0%

' SFMOG : 초고속 MOG 기반 배경 제거 알고리즘' 의 참고문헌

  • WeSamBE: A Weight-Sample-Based Method for Background Subtraction
  • Traditional and recent approaches in background modeling for foreground detection: An overview
  • Toward a Unified Color Space for Perception-Based Image Processing
    I. Lissner [2012]
  • SuBSENSE: A Universal Change Detection Method with Local Adaptive Sensitivity
  • Static and Moving Object Detection Using Flux Tensor with Split Gaussian Models
    R. Wang [2014]
  • Spatial mixture of Gaussians for dynamic background modelling
  • Region-based Mixture of Gaussians modelling for foreground detection in dynamic scenes
  • Recent Advanced Statistical Background Modeling for Foreground Detection - A Systematic Survey
  • Moving object detection usinglab2000hl color space with spatial and temporal smoothing
    M. Balcilar [2014]
  • Efficient adaptive density estimation per image pixel for the task of background subtraction
  • Detecting Moving Objects, Ghosts, and Shadows in Video Streams
  • Comparative study of motion detection methods for video surveillance systems
  • Combination of Video Change Detection Algorithms by Genetic Programming
  • CDnet 2014: An Expanded Change Detection Benchmark Dataset
    Y. Wang [2014]
  • Background subtraction in real applications: Challenges, current models and future directions
  • Background Modeling using Mixture of Gaussians for Foreground Detection - A Survey
  • BMOG: Boosted Gaussian Mixture Model with Controlled Complexity
    I. Martins [2017]
  • Adaptive background mixture models for real-time tracking
    C. Stauffer [1999]
  • A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos
  • A Self-Adjusting Approach to Change Detection Based on Background Word Consensus