Abstract
In recent years, moving cast shadow detection has become a critical challenge in improving the accuracy of moving object detection in video surveillance. In this paper, we propose two novel moving cast shadow detection methods based on nonnegative matrix factorization (NMF) and block nonnegative matrix factorization (BNMF). First, the algorithm of moving cast shadow detection using NMF is given and the key points such as the determination of moving shadow areas and the choice of discriminant function are specified. Then BNMF are introduced so that the new training samples and new classes can be added constantly with lower computational complexity. Finally, the improved shadow detection method is detailed described according to BNMF. The effectiveness of proposed methods is evaluated in various scenes. Experimental results demonstrate that the method achieves high detection rate and outperforms several state-of-the-art methods.
Original language | English |
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Pages (from-to) | 229-234 |
Number of pages | 6 |
Journal | Bulletin of the Polish Academy of Sciences: Technical Sciences |
Volume | 66 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2018 |
Bibliographical note
Publisher Copyright:© 2018 De Gruyter Open Ltd. All rights reserved.
Keywords
- Block nonnegative matrix factorization
- Moving cast shadow detection
- Nonnegative matrix factorization
- Video surveillance
ASJC Scopus subject areas
- General Engineering
- Artificial Intelligence
- Information Systems
- Atomic and Molecular Physics, and Optics
- Computer Networks and Communications