Reading list about automated visual systems

Here is a tentative reading list about automated visual systems (e.g. object detection, tracking, and recognition):

• T. Bouwmans, N. Aybat, and E. Zahzah. Handbook on "Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing", CRC Press, Taylor and Francis Group, May 2016: "shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications."
• T. Bouwmans, F. Porikli, B. Horferlin, A. Vacavant, Handbook on "Background Modeling and Foreground Detection for Video Surveillance: Traditional and Recent Approaches, Implementations, Benchmarking and Evaluation", CRC Press, Taylor and Francis Group, June 2014: "provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection."
• Soharab Hossain Shaikh, Khalid Saeed, Nabendu Chaki, Moving Object Detection Using Background Subtraction (SpringerBriefs in Computer Science), Springer, June 2014: "comprehensive survey of the existing methodologies of background subtraction methods", only 67 pages
• Vijayan K. Asari (Editor), Wide Area Surveillance: Real-time Motion Detection Systems (Augmented Vision and Reality), Springer, November 2013: "describes a system for visual surveillance using intelligent cameras. The camera uses robust techniques for detecting and tracking moving objects."
• Boguslaw Cyganek, Object Detection and Recognition in Digital Images: Theory and Practice, Wiley, August 2013: "provides the reader with a balanced treatment between the theory and practice of selected methods in these areas" (i.e. object detection, tracking and recognition in images).
• Jean-Yves Dufour (Editor), Intelligent Video Surveillance Systems, Wiley-ISTE, December 2012: "technical topics are discussed – the analysis of objects of interest (detection, tracking and recognition), “high-level” video analysis, which aims to give a semantic interpretation of the observed scene (events, behaviors, types of content)."
• Ester Martínez-Martín, Ángel P. del Pobil, Robust Motion Detection in Real-Life Scenarios, Springer, July 2012: "proposes a complete sensor-independent visual system that provides robust target motion detection."

Some interesting websites about automated visual systems:

• Background Subtraction Website (T. Bouwmans, Univ. La Rochelle, France): presents background subtraction methods, and their references
• Wikipedia article about Background substraction: in particular check the section Resources, datasets, and libraries

Survey papers about background substraction methods:

• T. Bouwmans, Traditional and Recent Approaches in Background Modeling for Foreground Detection: An Overview, Computer Science Review, 2014. [pdf]
• T. Bouwmans, E. Zahzah, Robust PCA via Principal Component Pursuit: A Review for a Comparative Evaluation in Video Surveillance, Special Issue on Background Models Challenge, Computer Vision and Image Understanding, CVIU 2014, Volume 122, pages 22–34, May 2014. [pdf]
• T. Bouwmans, Recent Advanced Statistical Background Modeling for Foreground Detection: A Systematic Survey, Recent Patents on Computer Science, Volume 4, No. 3, pages147-176, September 2011. [pdf]

Eventually I will post a more thorough reading list including also important research articles, and online tutorials about the topic of automated visual systems.