A novel bifold-stage shot boundary detection algorithm: invariant to motion and illumination

Author(s):  
Saptarshi Chakraborty ◽  
Alok Singh ◽  
Dalton Meitei Thounaojam
2009 ◽  
Vol 1 (2) ◽  
pp. 70-78 ◽  
Author(s):  
L. Xiang-Wei ◽  
L. Zhan-Ming ◽  
Z. Ming-Xin ◽  
Z. Ya-lLn ◽  
W. Wei-Yi

2013 ◽  
Vol 347-350 ◽  
pp. 3866-3871
Author(s):  
Kai Jin ◽  
Hong Cai Feng ◽  
Qi Feng ◽  
Chi Zhang

To establish a general and robust shot boundary detection algorithm, according to characteristics of lens conversion and the ideal of multiple video features fusion, a shot boundary detection algorithm is proposed based on YUV histogram, texture feature and edge orientation histogram in the paper. Besides, global and self-adaptive threshold are combined to use so as to control the process of shot boundary detection and enhance the accuracy of threshold selection. The experiment results show that the algorithm can effectively realize video shot boundary detection and strengthen the robustness of the detection.


Author(s):  
Mohammad A. Al-Jarrah ◽  
Faruq A. Al-Omari

A video is composed of set of shots, where shot is defined as a sequence of consecutive frames captured by one camera without interruption. In video shot transition could be a prompt (hard cut) or gradual (fade, dissolve, and wipe). Shot boundary detection is an essential component of video processing. These boundaries are utilized on many aspect of video processing such as video indexing, and video in demand. In this paper, the authors proposed a new shot boundary detection algorithm. The proposed algorithm detects all type of shot boundaries in a high accuracy. The algorithm is developed based on a global stochastic model for video stream. The proposed stochastic model utilizes the joined characteristic function and consequently the joined momentum to model the video stream. The proposed algorithm is implemented and tested against different types of categorized videos. The proposed algorithm detects cuts fades, dissolves, and wipes transitions. Experimental results show that the algorithm has high performance. The computed precision and recall rates validated its performance.


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