GOP Adaptation Coding of H.264/SVC Based on Precise Positions of Video Cuts = GOP Adaptation Coding of H.264/SVC Based on Precise Positions of Video Cuts

다국어 초록 (Multilingual Abstract)

Hierarchical B-frame coding was introduced into H.264/SVC to provide temporal scalability and improve coding performance. A content analysis-based adaptive group of picture structure (AGS) can further improve the coding efficiency, but damages the inter-frame correlation and temporal scalability of hierarchical B-frame to different degrees. In this paper, we propose a group of pictures (GOP) adaptation coding method based on the positions of video cuts. First, the cut positions are accurately detected by the combination of motion coherence (MC) and mutual information (MI); then the GOP is adaptively and proportionately set by the analysis of MC in one scene. In addition, we propose a binary tree algorithm to achieve the temporal scalability of any size of GOP. The results for test sequences and real videos show that the proposed method reduces the bit rate by up to about 15%, achieves a performance gain of about 0.28-1.67 dB over a fixed GOP, and has the advantages of better transmission resilience and video summaries.

참고문헌 (Reference)

1 Angadi Shanmukhappa, "Shot boundary detection and key frame extraction for sports video summarization based on spectral entropy and mutual information" 221 (221): 81-97, 2013

2 Yu Zhenyu, "Scene change detection using motion vectors and DC components of prediction residual in H.264 compressed videos" 990-995, 2012

3 H. Schwarz, "Overview of the scalable video coding extension of the H.264/AVC standard" 17 (17): 1103-1120, 2007

4 Nourani Vatani Navid, "On the use of optical flow for scene change detection and description" 2013

5 Ding JunRen, "Motion-based adaptive GOP algorithms for efficient H.264/AVC compression" 1-4, 2006

6 I. Radwan Nisreen, "Histogram correlation for video scene change detection" 166 (166): 765-773, 2012

7 B. Zatt, "GOP structure adaptive to the video content for efficient H.264/AVC encoding" 3053-3056, 2010

8 Lenka Krulikovsk´a, "GOP structure adaptable to the location of shot cuts" 58 (58): 129-134, 2012

9 YiHau Chen, "Fast prediction algorithm of adaptive GOP structure for SVC" 1-9, 2007

10 Paul Manoranjan, "Explore and model better I-frames for video coding" 21 (21): 1242-1254, 2011

11 T. M. Cover, "Elements of Information Theroy" Wiley 1991

12 Ling Zi, "Efficiency of dynamic GOP length in video stream" 765 (765): 879-884, 2013

13 S Paschalakis, "Detection of gradual transitions in video sequences"

14 Masala Enrico, "Content-based group-of-picture size control in distributed video coding" 29 (29): 332-344, 2014

15 Tian Song, "Coding efficiency improvement with adaptive GOP selection for H.264/SVC" 5 (5): 4155-4165, 2009

16 Hsiao HsuFeng, "Balanced parallel scheduling for video encoding with adaptive GOP structure" 24 (24): 2355-2364, 2013

17 Viral B Thakar, "An adaptive novel feature based approach for automatic video shot boundary detection" 145-149, 2013

18 M. W. Park, "Adaptive GOP structure for joint scalable video coding" 90 (90): 431-434, 2007

19 Chen HungWei, "Adaptive GOP structure determination in hierarchical B picture coding for the extension of H.264/AVC" 697-701, 2008

20 Ma Yanzhuo, "Adaptive GOP structure based on motion coherence" 1-8, 2009

21 Hamidreza Rashidy Kanan, "AVCD-FRA: A novel solution to automatic video cut detection using fuzzy-rule-based approach" 117 (117): 807-817, 2013

22 Birinci Murat, "A perceptual scheme for fully automatic video shot boundary detection" 29 (29): 410-423, 2014

23 Lenka Krulikovská, "A novel method of adaptive GOP structure based on the positions of video cuts" 67-70, 2011