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.
Moving Object Detection Using Background Subtraction
Format
Trade Paperback
Language
English
Publication Year
2014
Series
Springerbriefs in Computer Science Ser.
Type
Textbook
Number of Pages
X, 67 Pages
Dimensions
Item Length
9.3in
Item Width
6.1in
Item Weight
47.9 Oz
Additional Product Features
Number of Volumes
1 Vol.
Lc Classification Number
Ta1501-1820
Table of Content
Introduction.- Moving Object Detection Approaches, Challenges and Object Tracking.- Moving Object Detection Using Background Subtraction.- Moving Object Detection: A New Approach.- Databases for Research.- Conclusion.