Video summarisation using optimum global threshold technique based on genetic algorithm. (2016)

• Record Type: Journal Article
• Authors: Phadikar, Amit; Kumar, Nishant; Phadikar, Baisakhi Sur; Maity, Goutam Kumar
• Is Part Of: International journal of innovative computing and applications. Volume 7:Number 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016
• Subjects: colour histograms -- edge histograms -- genetic algorithms -- video summarisation -- optimum global threshold -- video summary generation -- key frames; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Most of the methods for video summarisation rely on complicated clustering algorithms that make them too computationally complex for real time applications. This paper presents an efficient approach for video summary generation that does not rely on complex clustering algorithms and does not require frame length as a parameter. The present scheme combines colour histogram and edge histogram features with optimum global thresholding to detect key frames. The optimum threshold is selected based on genetic algorithm (GA) to increase the performance of the proposed system. For each shot, key frames are extracted and similar key frames are eliminated. Experimental results duly support those claims.