Video Shot Boundary Detection � Comparision of Color Histogram and Gist Method

2012 ◽  
Vol 1 (1) ◽  
pp. 11-19
Author(s):  
P. Swati Sowjanya ◽  
Ravi Mishra
Keyword(s):  
Boundary Detection ◽  
Color Histogram ◽  
Shot Boundary Detection ◽  
Video Shot ◽  
Shot Boundary

An Improved Algorithm of Video Shot Boundary Detection

2011 ◽  
Vol 403-408 ◽  
pp. 1258-1261
Author(s):  
Jian Feng Zhang ◽  
Zhi Qiang Wei ◽  
Shu Ming Jiang ◽  
Jian Li ◽  
Shi Jie Xu ◽  
...  
Keyword(s):  
Error Rate ◽  
Video Processing ◽  
Boundary Detection ◽  
Local Information ◽  
Color Histogram ◽  
Shot Boundary Detection ◽  
Global Information ◽  
Threshold Algorithm ◽  
Video Shot ◽  
Shot Boundary

Shot boundary detection is the first step of the video processing. Based on the summary of the existing methods of shot boundary detection, this paper put forward an adaptive dual threshold algorithm which adjusts automatically the threshold along with the changes of the content of shots. Color histogram of weighted non-uniform blocks is taken as characteristic to calculate differences of frames in the algorithm, which considers not only the global information of the image, but also the local information. The second detection is carried on when the boundaries are detected initially reduces effectively error rate that caused by flashlight. Finally, the algorithm is proved effective.

Color-Based Video Shot Boundary Detection

2006 ◽  
pp. 525-548
Author(s):  
Nikos Nikolaidis ◽  
Costas Cotsaces ◽  
Zuzana Cernekova ◽  
Ioannis Pitas
Keyword(s):  
Boundary Detection ◽  
Shot Boundary Detection ◽  
Video Shot ◽  
Shot Boundary

Effective Video Shot Boundary Detection and Keyframe Selection using Soft Computing Techniques

2018 ◽  
Vol 8 (2) ◽  
pp. 27-48 ◽  
Author(s):  
Rashmi B S ◽  
Nagendraswamy H S
Keyword(s):  
Fuzzy Sets ◽  
Video Analysis ◽  
Boundary Detection ◽  
Extraction Methods ◽  
Video Data ◽  
Shot Boundary Detection ◽  
Keyframe Extraction ◽  
Soft Computing Techniques ◽  
Video Shot ◽  
Shot Boundary

The amount of video data generated and made publicly available has been tremendously increased in today's digital era. Analyzing these huge video repositories require effective and efficient content-based video analysis systems. Shot boundary detection and Keyframe extraction are the two major tasks in video analysis. In this direction, a method for detecting abrupt shot boundaries and extracting representative keyframe from each video shot is proposed. These objectives are achieved by incorporating the concepts of fuzzy sets and intuitionistic fuzzy sets. Shot boundaries are detected using coefficient of correlation on fuzzified frames. Further, probabilistic entropy measures are computed to extract the keyframe within fuzzified frames of a shot. The keyframe representative of a shot is the frame with highest entropy value. To show the efficacy of the proposed methods two benchmark datasets are used (TRECVID and Open Video Project). The proposed methods outperform when compared with some of state-of-the-art shot boundary detection and keyframe extraction methods.

Sign in / Sign up

Export Citation Format

Share Document