3D Local Spatio-temporal Ternary Patterns for Moving Object Detection in Complex Scenes-Reference-Cited by-同舟云学术

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3D Local Spatio-temporal Ternary Patterns for Moving Object Detection in Complex Scenes

Published:2018-09-14 Issue:1 Volume:11 Page:18-30
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Vasamsetti Srikanth,Mittal Neerja,Neelapu Bala Chakravarthy,Sardana Harish Kumar

Funder

Council of Scientific and Industrial Research

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

http://link.springer.com/article/10.1007/s12559-018-9594-5/fulltext.html

Reference40 articles.

1. Akilan T, Wu QJ, Yang Y. Fusion-based foreground enhancement for background subtraction using multivariate multi-model gaussian distribution. Inf Sci 2018;430:414–31.

2. Bouwmans T, El Baf F, Vachon B. Background modeling using mixture of gaussians for foreground detection-a survey. Recent Patents on Computer Science 2008;1(3):219–37.

3. El Baf F, Bouwmans T, Vachon B. Fuzzy integral for moving object detection. IEEE international conference on Fuzzy systems, 2008. FUZZ-IEEE 2008.(IEEE world congress on computational intelligence). IEEE; 2008. p. 1729–36.

4. Goyette N, Jodoin PM, Porikli F, Konrad J, Ishwar P. Changedetection. net: a new change detection benchmark dataset. 2012 IEEE computer society conference on computer vision and pattern recognition workshops (CVPRW). IEEE; 2012. p. 1–8.

5. Guo JM, Liu YF, Hsia CH, Shih MH, Hsu CS. Hierarchical method for foreground detection using codebook model. IEEE Transactions on Circuits and Systems for Video Technology 2011;21(6):804–15.

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