A motion constraint equation under space-varying or time-varying illumination
Pattern Recognition Letters
A fast thresholding selection procedure for multimodal and unimodal histograms
Pattern Recognition Letters
A neural-vision based approach to measure traffic queue parameters in real-time
Pattern Recognition Letters
Background subtraction based on logarithmic intensities
Pattern Recognition Letters
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Moving object segmentation by background subtraction and temporal analysis
Image and Vision Computing
Spatio-temporal reasoning for the classification of satellite image time series
Pattern Recognition Letters
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Motion detection is widely used as the key module for moving object extraction from image frames. In most of the motion detection methods, backgrounds are subtracted from captured images. This is called background subtraction. As standard intensity can be expressed as the multiplication of illumination and reflectance, illumination changes will produce a poor difference image from background subtraction and affect the accuracy of motion detection. In this paper, we use ratio images as the basis for motion detection. For thresholding the target images, we propose change-point detection for cumulative histograms to prevent the difficulties of searching peaks and valleys in histograms. Experimental results show that change-point detection of cumulative histograms performs very well for thresholding the target images. In addition, the superiority of motion detection based on ratio images to motion detection based on difference images is also depicted in experimentation.