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Spatiotemporal approach for tracking using rough entropy and frame subtraction

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TLDR
An approach for video image segmentation where spatial segmentation is based on rough sets and granular computing and temporal segmentation was done by consecutive frame subtraction is presented.
Abstract
We present here an approach for video image segmentation where spatial segmentation is based on rough sets and granular computing and temporal segmentation is done by consecutive frame subtraction. Then the intersection of the temporal segmentation and spatial segmentation for the same frame is analyzed in RGB feature space. The estimated statistics of the intersecting regions is used for the object reconstruction and tracking.

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Journal ArticleDOI

Granulation, rough entropy and spatiotemporal moving object detection

TL;DR: A new spatio-temporal segmentation approach for moving object(s) detection and tracking from a video sequence is described, which is more robust to noise and gradual illumination change, and superior to several related methods.
References
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Book

Rough Sets: Theoretical Aspects of Reasoning about Data

TL;DR: Theoretical Foundations.
Journal ArticleDOI

Object tracking: A survey

TL;DR: The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends to discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.
Book

Digital Video Processing

TL;DR: Digital Video Processing, Second Edition, reflects important advances in image processing, computer vision, and video compression, including new applications such as digital cinema, ultra-high-resolution video, and 3D video.
Book

Video Tracking: Theory and Practice

TL;DR: The design methodologies discussed throughout the book provide guidelines for developers in the industry working on vision-based applications, and help researchers and practitioners develop techniques and solutions based on the potential of video tracking applications.