Dorfeshan, N., Ramezanpour, M. (2018). Compressed Domain Scene Change Detection Based on Transform Units Distribution in High Efficiency Video Coding Standard. Journal of Computer & Robotics, 11(2), 41-48.
Navid Dorfeshan; Mohammadreza Ramezanpour. "Compressed Domain Scene Change Detection Based on Transform Units Distribution in High Efficiency Video Coding Standard". Journal of Computer & Robotics, 11, 2, 2018, 41-48.
Dorfeshan, N., Ramezanpour, M. (2018). 'Compressed Domain Scene Change Detection Based on Transform Units Distribution in High Efficiency Video Coding Standard', Journal of Computer & Robotics, 11(2), pp. 41-48.
Dorfeshan, N., Ramezanpour, M. Compressed Domain Scene Change Detection Based on Transform Units Distribution in High Efficiency Video Coding Standard. Journal of Computer & Robotics, 2018; 11(2): 41-48.
Compressed Domain Scene Change Detection Based on Transform Units Distribution in High Efficiency Video Coding Standard
1Department of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2Department of Computer Engineering, Mobarakeh Branch, Islamic Azad University, Mobarakeh, Isfahan, Iran
Receive Date: 25 May 2018,
Revise Date: 31 July 2018,
Accept Date: 02 September 2018
Abstract
Scene change detection plays an important role in a number of video applications, including video indexing, searching, browsing, semantic features extraction, and, in general, pre-processing and post-processing operations. Several scene change detection methods have been proposed in different coding standards. Most of them use fixed thresholds for the similarity metrics to determine if there was a change or not. These thresholds are obtained empirically or they must be calculated before the scene change detection after the whole sequence is obtained. Efficiency of scene change detectors decreases considerably for videos with high scene complexity and variation. In this paper, we propose a novel scene change detection algorithm in the HEVC compressed domain. In the proposed method, we have developed an efficient method based on the analysis of the Transform Units distribution in HEVC standard. In order to enhance the accuracy of detecting the scene changes, we have also defined an automated, dynamic threshold model which can efficiently trace scene changes. The experimental results on UHD videos indicate a higher performance with significantly improved accuracy combined with minimum complexity.
Top