Moving Object Detection for Dynamic Background Scenes Based on Spatiotemporal Model
Joint Authors
Yang, Yizhong
Zhang, Qiang
Wang, Pengfei
Hu, Xionglou
Wu, Nengju
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-06-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Moving object detection in video streams is the first step of many computer vision applications.
Background modeling and subtraction for moving detection is the most common technique for detecting, while how to detect moving objects correctly is still a challenge.
Some methods initialize the background model at each pixel in the first N frames.
However, it cannot perform well in dynamic background scenes since the background model only contains temporal features.
Herein, a novel pixelwise and nonparametric moving object detection method is proposed, which contains both spatial and temporal features.
The proposed method can accurately detect the dynamic background.
Additionally, several new mechanisms are also proposed to maintain and update the background model.
The experimental results based on image sequences in public datasets show that the proposed method provides the robustness and effectiveness in dynamic background scenes compared with the existing methods.
American Psychological Association (APA)
Yang, Yizhong& Zhang, Qiang& Wang, Pengfei& Hu, Xionglou& Wu, Nengju. 2017. Moving Object Detection for Dynamic Background Scenes Based on Spatiotemporal Model. Advances in Multimedia،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1122351
Modern Language Association (MLA)
Yang, Yizhong…[et al.]. Moving Object Detection for Dynamic Background Scenes Based on Spatiotemporal Model. Advances in Multimedia No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1122351
American Medical Association (AMA)
Yang, Yizhong& Zhang, Qiang& Wang, Pengfei& Hu, Xionglou& Wu, Nengju. Moving Object Detection for Dynamic Background Scenes Based on Spatiotemporal Model. Advances in Multimedia. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1122351
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1122351