Moving Object Detection Using Background Subtraction

Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Application Software, Computer Graphics, General Computing
Cover of the book Moving Object Detection Using Background Subtraction by Soharab Hossain Shaikh, Khalid Saeed, Nabendu Chaki, Springer International Publishing
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Author: Soharab Hossain Shaikh, Khalid Saeed, Nabendu Chaki ISBN: 9783319073866
Publisher: Springer International Publishing Publication: June 20, 2014
Imprint: Springer Language: English
Author: Soharab Hossain Shaikh, Khalid Saeed, Nabendu Chaki
ISBN: 9783319073866
Publisher: Springer International Publishing
Publication: June 20, 2014
Imprint: Springer
Language: English

This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.

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This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.

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