A Novel Feature Weighted Clustering Algorithm Based on Rough Sets for Shot Boundary Detection

2006 ◽  
pp. 471-480 ◽  
Author(s):  
Bing Han ◽  
Xinbo Gao ◽  
Hongbing Ji
Keyword(s):  
Rough Sets ◽  
Clustering Algorithm ◽  
Boundary Detection ◽  
Shot Boundary Detection ◽  
Weighted Clustering ◽  
Shot Boundary

Rapid Shot Boundary Detection Algorithm Based on Rough Sets in Video Compressed Domain

2009 ◽  
Vol 1 (2) ◽  
pp. 70-78 ◽  
Author(s):  
L. Xiang-Wei ◽  
L. Zhan-Ming ◽  
Z. Ming-Xin ◽  
Z. Ya-lLn ◽  
W. Wei-Yi
Keyword(s):  
Rough Sets ◽  
Boundary Detection ◽  
Detection Algorithm ◽  
Shot Boundary Detection ◽  
Compressed Domain ◽  
Shot Boundary

An Efficient Shot Boundary Detection Using Data-cube Searching Technique

2020 ◽  
Vol 13 (4) ◽  
pp. 798-807
Author(s):  
J. Kavitha ◽  
P. Arockia Jansi Rani ◽  
P. Mohamed Fathimal ◽  
Asha Paul
Keyword(s):  
Texture Features ◽  
Boundary Detection ◽  
Data Cube ◽  
Multimedia Data ◽  
Shot Boundary Detection ◽  
Gradual Transition ◽  
Detection Rates ◽  
Effective Manner ◽  
Shot Boundary ◽  
Shot Transitions

Background:: In the internet era, there is a prime need to access and manage the huge volume of multimedia data in an effective manner. Shot is a sequence of frames captured by a single camera in an uninterrupted space and time. Shot detection is suitable for various applications such that video browsing, video indexing, content based video retrieval and video summarization. Objective:: To detect the shot transitions in the video within a short duration. It compares the visual features of frames like correlation, histogram and texture features only in the candidate region frames instead of comparing the full frames in the video file. Methods: This paper analyses candidate frames by searching the values of frame features which matches with the abrupt detector followed by the correct cut transition frame with in the datacube recursively until it detects the correct transition frame. If they are matched with the gradual detector, then it will give the gradual transition ranges, otherwise the algorithm will compare the frames within the next datacube to detect shot transition. Results:: The total average detection rates of all transitions computed in the proposed Data-cube Search Based Shot Boundary Detection technique are 92.06 for precision, 96.92 for recall and 93.94 for f1 measure and the maximum accurate detection rate. Conclusion:: Proposed method for shot transitions uses correlation value for searching procedure with less computation time than the existing methods which compares every single frame and uses multi features such as color, edge, motion and texture features in wavelet domain.

RELIABLE TRANSITION DETECTION IN VIDEOS: A SURVEY AND PRACTITIONER'S GUIDE

2001 ◽  
Vol 01 (03) ◽  
pp. 469-486 ◽  
Author(s):  
RAINER LIENHART
Keyword(s):  
Video Processing ◽  
Boundary Detection ◽  
Shot Boundary Detection ◽  
Detection Techniques ◽  
Core Concepts ◽  
Reliable Performance ◽  
Shot Boundary ◽  
Transition Effects ◽  
Detection Schemes

A large number of shot boundary detection, or equivalently, transition detection techniques have been developed in recent years. They all can be classified based on a few core concepts underlying the different detection schemes. This survey emphasizes those different core concepts underlying the different detection schemes for the three most widely used video transition effects: hard cuts, fades and dissolves. Representative of each concept one or a few very sound and thoroughly tested approaches are present in detail, while others are just listed. Whenever reliable performance numbers could be found in the literature, they are mentioned. Guidelines for practitioners in video processing are also given.

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