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

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.

2017 ◽  
Vol 17 (01) ◽  
pp. 1750002 ◽  
Author(s):  
J. Kavitha ◽  
P. Arockia Jansi Rani ◽  
S. Sowmyayani

The objective of this paper is to develop a shot boundary detection system to detect shots from a given video. To meet this objective, it is proposed to use feature vector in the process of identifying cut transition and gradual transition. The proposed method analyzes each video frame with its immediate left and right neighbor frame and identifies shot transitions. For each frame comparison, it considers color, edge, motion, and texture features of left and right frames. The proposed method is evaluated on video sequences from the TRECVID video set. The experimental results of the proposed method are compared with the existing methods. It is observed that the proposed method is suitable to perform robust shot boundary detection.


2020 ◽  
Vol 8 (5) ◽  
pp. 4763-4769

Now days as the progress of digital image technology, video files raise fast, there is a great demand for automatic video semantic study in many scenes, such as video semantic understanding, content-based analysis, video retrieval. Shot boundary detection is an elementary step for video analysis. However, recent methods are time consuming and perform badly in the gradual transition detection. In this paper we have projected a novel approach for video shot boundary detection using CNN which is based on feature extraction. We designed couple of steps to implement this method for automatic video shot boundary detection (VSBD). Primarily features are extracted using H, V&S parameters based on mean log difference along with implementation of histogram distribution function. This feature is given as an input to CNN algorithm which detects shots which is based on probability function. CNN is implemented using convolution and rectifier linear unit activation matrix which is followed after filter application and zero padding. After downsizing the matrix it is given as a input to fully connected layer which indicates shot boundaries comparing the proposed method with CNN method based on GPU the results are encouraging with substantially high values of precision Recall & F1 measures. CNN methods perform moderately better for animated videos while it excels for complex video which is observed in the results.


2001 ◽  
Vol 01 (03) ◽  
pp. 469-486 ◽  
Author(s):  
RAINER LIENHART

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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