Robust techniques for background subtraction in urban traffic video

By S. Cheung, Chandrika Kamath. IS&T/SPIE Electronic Imaging, 2004

881 citations recorded by the source corpus.

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Cyclops: in situ image sensing and interpretation in wireless sensor networks (2005, methodology): “There are many ways to approach this problem and we chose the basic method [12] to minimize computation requirements.”
Comparative study of background subtraction algorithms (2010, background): “This solution has proven successful whenever the camera is rigorously static with a fixed noise-free background (see [9] for some examples).”
Fuzzy human motion analysis: A review (2014, methodology): “The studies on the background subtraction [56, 57] have show n that the Gaussian Mixture Model (GMM) is one of the popular approaches used in modeling the dynamic backg round scene.”
Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art (2008, methodology): “Cheung and Kamath [4] suggest another way of classification; they classify background adaptation techniques into two broad categories - non-recursive and recursive.”