Application of design of image tracking by combining SURF and TLD and SVM-based posture recognition system in robbery pre-alert system

Application of design of image tracking by combining SURF and TLD and SVM-based posture... This paper describes the design of an image tracking system that combines Speeded Up Robust Features (SURF) and Tracking-Learning-Detection (TLD), with a posture recognition system that is based on the Support Vector Machine (SVM), and includes image tracking, foreground detection and posture recognition. Image tracking, which combines the SURF and the TLD algorithms, starts by detecting the postures of a specific person with SURF, before tracking the object using TLD. Foreground detection uses the Codebook background subtraction algorithm to acquire foreground images and mends them by post-processing. Lastly, posture recognition applies SVM to determine human body postures. This article embodies such a system by applying it in a robbery pre-alert system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

Application of design of image tracking by combining SURF and TLD and SVM-based posture recognition system in robbery pre-alert system

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-017-4449-8
Publisher site
See Article on Publisher Site

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