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Patent

Motion detection using normal optical flow

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TLDR
In this paper, a histogram recognition operation is used to identify a motion of an object in a motion region image of the object. But the method is not suitable for the detection of human motion.
Abstract
A system and method obtain images of an object and generate a motion region image of the object. The motion region image is processed to obtain normal gradients of the portion of the object that has been moved. The normal gradient data is further processed to remove erroneous data points. The erroneous data can be removed by using either an eroding method or a threshold method. After the erroneous data is removed, the remaining gradient information is used to identify a motion of the object. This can be performed using a histogram recognition operation.

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References
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Journal ArticleDOI

Color indexing

TL;DR: In this paper, color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models, and they can differentiate among a large number of objects.

Computer Vision Face Tracking For Use in a Perceptual User Interface

TL;DR: The development of the first core module in this effort: a 4-degree of freedom color object tracker and its application to flesh-tone-based face tracking and the development of a robust nonparametric technique for climbing density gradients to find the mode of a color distribution within a video scene.
Book

Algorithms for image processing and computer vision

TL;DR: Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.
Proceedings ArticleDOI

Color gamut transform pairs

TL;DR: A set of alternative models of the RGB monitor gamut based on the perceptual variables hue, saturation, and value (V) or brightness (L) are presented and algorithms for transforming between these models are derived.