DWT-Based Shot Boundary Detection Using Support Vector Machine

Video shot detection is an important contemporary problem since it is the first step toward automatic indexing, content based video retrieval and many other different applications. A novel shot boundary detection using wavelet and Support Vector Machine is proposed in this paper. Shot boundary detec...

Full description

Saved in:
Bibliographic Details
Published in2009 Fifth International Conference on Information Assurance and Security Vol. 1; pp. 435 - 438
Main Authors Jun Li, Youdong Ding, Yunyu Shi, Qingyue Zeng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Color
Computer security
Detection algorithms
Discrete wavelet transforms
DWT
Feature extraction
Frequency
Gunshot detection systems
Information retrieval
Shot Boundary Detection
Support Vector Machine
Support vector machine classification
Support vector machines
Online AccessGet full text

Cover

More Information
Summary:Video shot detection is an important contemporary problem since it is the first step toward automatic indexing, content based video retrieval and many other different applications. A novel shot boundary detection using wavelet and Support Vector Machine is proposed in this paper. Shot boundary detection algorithms work by extracting the color and the edge in different direction from wavelet transition coefficients. A multi-class support vector machine (SVM) classifier is used to classify the video shot into three categories: cut transition(CT), gradual transition(GT) and normal sequences (NF). To enhance the robustness of the algorithm, we form the feature vector from all frames within a temporal window. Numerical experiments using a variety of videos demonstrate that our method is capable of accurately detecting and discriminating shot transitions in videos with different characteristics.
ISBN:0769537448
9780769537443
DOI:10.1109/IAS.2009.16