Video shot boundary detection based on MB coding mode and SIFT features on H.264/AVC

2014 ◽  
Author(s):  
Qingming Zhang
Keyword(s):  
Boundary Detection ◽  
Shot Boundary Detection ◽  
Video Shot ◽  
Shot Boundary ◽  
Sift Features ◽  
Coding Mode

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