NDLI: Moving shadow detection via binocular vision and colour clustering

Content Provider	IET Digital Library
Author	Lu, Lei Xu, Ming Smith, Jeremy S. Yan, Yuyao
Abstract	A pedestrian segmentation algorithm in the presence of cast shadows is presented in this study. The novelty of this algorithm lies in the fusion of multi-view and multi-plane homographic projections of foregrounds and the use of the fused data to guide colour clustering. This brings about an advantage over the existing binocular algorithms in that it can remove cast shadows while keeping pedestrians’ body parts, which occlude shadows. Phantom detection, which is inherent with the binocular method, is also investigated. Experimental results with real-world videos have demonstrated the efficiency of this algorithm.
Starting Page	665
Ending Page	673
Page Count	9
ISSN	17519632
Volume Number	14
e-ISSN	17519640
Issue Number	Issue 8, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/14/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2019.0175
Journal	IET Computer Vision
Publisher Date	2020-10-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Binocular Method Binocular Vision Cast Shadows Colour Clustering Computer Vision Computer Vision And Image Processing Technique Existing Binocular Algorithm Fused Data Image Colour Analysis Image Motion Analysis Image Segmentation Image Sequence Multiview Object Detection Optical, Image And Video Signal Processing Pedestrian Pedestrian Segmentation Algorithm Phantom Detection Shadow Detection Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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