Background subtraction

Last updated Nov 14, 2024 Edit Source

• https://en.wikipedia.org/wiki/Foreground_detection
• https://github.com/murari023/awesome-background-subtraction
• Foreground detection is one of the major tasks in the field of computer vision and image processing whose aim is to detect changes in image sequences.
• Background subtraction is any technique which allows an image’s foreground to be extracted for further processing (object recognition etc.).
• Background Subtraction Website (T. Bouwmans)

• #BOOK Background modeling and Foreground Detection for video surveillance (Bouwmans, 2014 CRC)

• LRSlibrary
  • Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
• BGSlibrary
  • A C++ Background Subtraction Library with wrappers for Python, MATLAB, Java and GUI on QT

• #PAPER Mixture of Gaussians models. Adaptive background mixture models for real-time tracking (Straufer 1998)
• #PAPER ViBe: A Universal Background Subtraction Algorithm for Video Sequences (Barnich 2011)
• #PAPER PBAS - Background Segmentation with Feedback: The Pixel-Based Adaptive Segmenter (Hoffman 2012)
• #PAPER Background Subtraction For Visual Surveillance: A Fuzzy Approach (Bouwmans 2012)
  • http://www.academia.edu/download/36330997/ChapterFuzzy.pdf
• #PAPER Robust Principal Component Analysis for Background Subtraction: Systematic Evaluation and Comparative Analysis (Guyon 2012)
• #PAPER #REVIEW A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos (Sobral 2014)
• #PAPER #REVIEW Traditional and recent approaches in background modeling for foreground detection: An overview (Bouwmans 2014)

• #PAPER Deep background subtraction with scene-specific convolutional neural networks
• #PAPER A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction
• #PAPER Foreground Detection in Surveillance Video with Fully Convolutional Semantic Network
• #PAPER BSCGAN - Deep Background Subtraction with Conditional Generative Adversarial Networks
• #PAPER Interactive DL method for segmenting moving objects (Wang 2017)
• #PAPER Deep Neural Network Concepts for Background Subtraction: A Systematic Review and Comparative Evaluation (Bouwmans 2019)
• #PAPER Deep Learning based Background Subtraction: A Systematic Survey (Giraldo 2020)