Moving target segmentation using Markov random field-based evaluation metric in infrared videos-Reference-Cited by-同舟云学术

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Moving target segmentation using Markov random field-based evaluation metric in infrared videos

Published:2018-01-23 Issue:01 Volume:57 Page:1
ISSN:0091-3286
Container-title:Optical Engineering
language:
Short-container-title:Opt. Eng.

Author:

Sun Bin¹,Li Yingjie²,Guosheng Chen³,Zhang Junju²,Chang Bengkang²,Min Chaobo²

Affiliation:

1. Nanjing University of Posts and Telecommunications, School of Automation, Nanjing, Jiangsu Province

2. Nanjing University of Science and Technology, School of Electronic Engineering and Optic-Electronic

3. Northern Information Control Research Institute Group Co. Ltd., Nanjing, Jiangsu Province

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Engineering,Atomic and Molecular Physics, and Optics

Reference43 articles.

1. New method for the fusion of complementary information from infrared and visual images for object detection

2. Mean shift clustering-based moving object segmentation in the H.264 compressed domain

3. Fast infrared image segmentation algorithm;Shen,2005

4. Infrared image segmentation with 2D OTSU method based on particle swarm optimization

5. Infrared image segmentation with 2-D maximum entropy method based on particle swarm optimization (PSO)

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2. A motion-appearance-aware network for object change detection;Knowledge-Based Systems;2022-11

3. Interactive spatio-temporal feature learning network for video foreground detection;Complex & Intelligent Systems;2022-03-25

4. Sensor-based and vision-based human activity recognition: A comprehensive survey;Pattern Recognition;2020-12

5. A moving target extraction algorithm based on the fusion of infrared and visible images;Infrared Physics & Technology;2019-05

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