Total Variation Regularization Term-Based Low-Rank and Sparse Matrix Representation Model for Infrared Moving Target Tracking

Total Variation Regularization Term-Based Low-Rank and Sparse Matrix Representation Model for Infrared Moving Target Tracking

Infrared moving target tracking plays a fundamental role in many burgeoning research areas of Smart City. Challenges in developing a suitable tracker for infrared images are particularly caused by pose variation, occlusion, and noise. In order to overcome these adverse interferences, a total variati...

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Bibliographic Details
Main Authors:	Minjie Wan, Guohua Gu, Weixian Qian, Kan Ren, Qian Chen, Hai Zhang, Xavier Maldague
Format:	Article
Language:	English
Published:	MDPI AG 2018-03-01
Series:	Remote Sensing
Subjects:	infrared moving target tracking low-rank and sparse matrix representation total variation regularization particle filtering framework Smart City
Online Access:	http://www.mdpi.com/2072-4292/10/4/510

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