Robust Shot Boundary Detection from Video Using Dynamic Texture

Video boundary detection belongs to a basis subject in computer vision. It is more important to video analysis and video understanding. The existing video boundary detection methods always are effective to certain types of video data. These methods have relatively low generalization ability. We pres...

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Published inSensors & transducers Vol. 167; no. 3; p. 104
Main Authors Taile, Peng, Wenjun, Zhang
Format Journal Article
LanguageEnglish
Published Toronto IFSA Publishing, S.L 01.03.2014
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ISSN2306-8515
1726-5479
1726-5479

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Abstract Video boundary detection belongs to a basis subject in computer vision. It is more important to video analysis and video understanding. The existing video boundary detection methods always are effective to certain types of video data. These methods have relatively low generalization ability. We present a novel shot boundary detection algorithm based on video dynamic texture. Firstly, the two adjacent frames are read from a given video. We normalize the two frames to get the same size frame. Secondly, we divide these frames into some sub-domain on the same standard. The following thing is to calculate the average gradient direction of sub-domain and form dynamic texture. Finally, the dynamic texture of adjacent frames is compared. We have done some experiments in different types of video data. These experimental results show that our method has high generalization ability. To different type of videos, our algorithm can achieve higher average precision and average recall relative to some algorithms. [PUBLICATION ABSTRACT]
AbstractList Video boundary detection belongs to a basis subject in computer vision. It is more important to video analysis and video understanding. The existing video boundary detection methods always are effective to certain types of video data. These methods have relatively low generalization ability. We present a novel shot boundary detection algorithm based on video dynamic texture. Firstly, the two adjacent frames are read from a given video. We normalize the two frames to get the same size frame. Secondly, we divide these frames into some sub-domain on the same standard. The following thing is to calculate the average gradient direction of sub-domain and form dynamic texture. Finally, the dynamic texture of adjacent frames is compared. We have done some experiments in different types of video data. These experimental results show that our method has high generalization ability. To different type of videos, our algorithm can achieve higher average precision and average recall relative to some algorithms. [PUBLICATION ABSTRACT]
Video boundary detection belongs to a basis subject in computer vision. It is more important to video analysis and video understanding. The existing video boundary detection methods always are effective to certain types of video data. These methods have relatively low generalization ability. We present a novel shot boundary detection algorithm based on video dynamic texture. Firstly, the two adjacent frames are read from a given video. We normalize the two frames to get the same size frame. Secondly, we divide these frames into some sub-domain on the same standard. The following thing is to calculate the average gradient direction of sub-domain and form dynamic texture. Finally, the dynamic texture of adjacent frames is compared. We have done some experiments in different types of video data. These experimental results show that our method has high generalization ability. To different type of videos, our algorithm can achieve higher average precision and average recall relative to some algorithms.
Author Wenjun, Zhang
Taile, Peng
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SubjectTerms Algorithms
Boundaries
Dynamics
Experiments
Frames
Shot
Surface layer
Texture
Video data
Title Robust Shot Boundary Detection from Video Using Dynamic Texture
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