以動量為基礎之快速多視角視訊編碼模式決策

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：65

、訪客IP：3.142.212.119

姓名

詹佳琦(Chia-Chi Chan) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

以動量為基礎之快速多視角視訊編碼模式決策
(Fast Mode Decision Using Motion Statistics for Multi-view Video Coding)

相關論文

★ 應用於車內視訊之光線適應性視訊壓縮編碼器設計	★ 以粒子濾波法為基礎之改良式頭部追蹤系統
★ 應用於空間與CGS可調性視訊編碼器之快速模式決策演算法	★ 應用於人臉表情辨識之強健式主動外觀模型搜尋演算法
★ 結合Epipolar Geometry為基礎之視角間預測與快速畫面間預測方向決策之多視角視訊編碼	★ 基於改良式可信度傳遞於同質區域之立體視覺匹配演算法
★ 以階層式Boosting演算法為基礎之棒球軌跡辨識	★ 多視角視訊編碼之快速參考畫面方向決策
★ 以線上統計為基礎應用於CGS可調式編碼器之快速模式決策	★ 適用於唇形辨識之改良式主動形狀模型匹配演算法
★ 以運動補償模型為基礎之移動式平台物件追蹤	★ 基於匹配代價之非對稱式立體匹配遮蔽偵測
★ 應用於地點影像辨識之快速局部L-SVMs群體分類器	★ 以高品質合成視角為導向之快速深度視訊編碼模式決策
★ 以運動補償模型為基礎之移動式相機多物件追蹤	★ 基於匹配代價曲線特徵之遮蔽偵測之研究

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

由於多視角視訊編碼運算複雜度極高，若需實現於消費電子產品中，須加速其執行，此可由演算法與硬體層進行。而為了讓快速演算法能夠適用於不同量化參數，本論文提出以運動向量差為基礎之快速模式決策演算法。本論文設計包含三個部分，由於最佳編碼模式的決定與RD cost有很高的關聯性且direct佔極高比例，因此第一部分演算法依據RD cost之統計分析針對direct模式進行加速，找出決定候選模式之臨界值與QP之間呈指數函數的關聯性，加速時針對不同QP的臨界值，可直接從指數函數中求得，並將RD cost與臨界值比較以減少測試其他Inter modes及Intra modes為候選編碼模式。由於最佳編碼模式的決定與運動估測之motion cost亦有很高的關聯性，因此第二部分依據motion cost之統計分析，找出決定候選模式集合之臨界值與QP之間呈指數函數的關聯性，加速時針對不同QP的臨界值，可直接從指數函數中求得，並將motion cost與臨界值比較以減少候選模式的選擇。第三部分為依運動向量差(motion vector difference, MVD)的動量資訊將待編碼區塊分為三種不同區域，藉由區塊特性進而減少Inter modes候選編碼模式的選擇。由修改JMVC 6.0編碼器之實驗結果顯示，本論文所提出之快速演算法平均可節省約70.79%，位元率平均下降約0.18%且PSNR平均下降約0.05dB。而與目前現有之多視角視訊之快速模式演算法相比，本論文能節省較多的編碼時間，且對RD performance幾乎不會造成影響。

摘要(英)

The high computational complexity of multi-view video codec makes it necessary to speed up for their realization in consumer electronics. In order to adapt a fast encoding algorithm to different quantization parameters (QP), we propose a fast mode decision algorithm using motion statistics for multi-view video coding. The fast algorithm is composed of two parts. First of all, whether direct mode will be determined as an optimal mode or not based on the statistical analysis of RD cost since an optimal mode has high correlation with RD cost. The thresholds can be derived from the exponential function having high correlation with QP and RD cost. Secondly, mode candidates are reduced based on the statistical analysis of motion cost since an optimal mode also has high correlation with motion cost. The thresholds can be derived from the exponential function having high correlation with QP and motion statistics. Finally, a current MB is classified into three different kinds of regions according to analysis of motion vector difference (MVD), and the candidates for mode decision are derived from the corresponding region. Our experimental results show that the proposed scheme reduces up to 70.79% of encoding time with only 0.05 dB loss in peak-to-noise ratio (PSNR) and 0.18% bitrate decrement compared with the original JMVC 6.0. Compared with other algorithms, the proposed algorithm can reduce more computational complexity with negligible degradation of coding efficiency.

關鍵字(中)

★ 運動向量差
★ 快速模式決策演算法

關鍵字(英)

★ motion vector difference
★ fast mode decision

論文目次

摘要 I
Abstract II
致謝 IV
圖目錄 VIII
表目錄 XI
第一章緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 研究方法 2
1.4 論文架構 3
第二章多視角視訊編碼器介紹 4
2.1 單視角視訊編碼器之相關技術現況 4
2.1.1 巨集區塊模式介紹 5
2.1.2 最佳預測模式決策 6
2.2 多視角視訊編碼器介紹 6
2.2.1 多視角視訊編碼器簡介 7
2.2.2 多視角視訊編碼器架構 8
2.2.3 增進多視角視訊編碼效率之工具 10
2.2.3.1 B-picture之Direct Mode 10
2.2.3.2運動估測(Motion Estimation)及視差估測(Disparity Estimation) 11
2.3 總結 12
第三章多視角視訊編碼之快速模式決策演算法現況 13
3.1 快速Direct Mode決策演算法 13
3.2 提早終止(Early Termination)模式決策演算法 15
3.3 以運動向量差為基礎之快速模式決策演算法 15
3.4 總結 17
第四章本論文提出之快速模式決策演算法 18
4.1本論文採用之多視角視訊編碼預測架構 18
4.2以RD Cost為基礎之快速模式決策演算法 19
4.2.1模式決策之RD cost統計分佈圖 20
4.2.2本論文提出之以RD Cost為基礎之快速模式決策演算法 26
4.3以Motion Cost為基礎之快速模式決策演算法 28
4.3.1運動估測之RD cost統計分佈圖 28
4.3.2本論文提出之以Motion Cost為基礎之快速模式決策演算法 38
4.4以運動向量差為基礎之快速模式決策演算法 45
4.4.1 最佳區塊模式與運動向量差之關聯性 46
4.4.2本論文提出之以運動向量差為基礎之快速模式決策演算法 50
4.5結合以Motion Cost、RD Cost及運動向量差為基礎之快速模式決策演算法 57
4.6 總結 58
第五章實驗結果與分析 59
5.1 實驗環境與參數設定 59
5.2以RD Cost為基礎之快速模式決策演算法(Fast Mode Decision Using the Statistical Analysis of RD cost) 61
5.3 以Motion Cost為基礎之快速模式決策演算法(Fast Mode Decision Using the Statistical Analysis of Motion Cost) 65
5.4以運動向量差為基礎之快速模式決策演算法(Fast Mode Decision Based on Motion Vector Difference) 70
5.5 結合以Motion Cost、RD Cost及運動向量差為基礎之快速模式決策演算法 (Fast Mode Decision Using Motion Statistics for Multi-view Video Coding) 73
5.6 總結 77
參考文獻 79
Publication 83

參考文獻

[1] ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, “JMVC 1.0 software,” JVT-AA212, Geneva, April 2008.
[2] Y.-S. Ho and K.-J. Oh, “Overview of multi-view video coding,” in Proceedings of IEEE International Workshop on Systems, Signals and Image Processing, pp. 5-12, June 2007.
[3] A. Smolic, K. Muller, P. Merkle, C. Fehn, P. Kauff, P. Eisert, and T. Wiegand, “3D video and free viewpoint video—technologies, applications and MPEG standards,” in Proceedings of IEEE International Conference on Multimedia and Exposition, pp. 2161-2164, July 2006.
[4] L. Onural, A. Smolic, and T. Sikora, “An overview of a new European consortium: integrated three-dimensional television—capture, transmission and display (3DTV),” in Proceedings of European Workshop on the Integration of Knowledge, Semantic and Digital Media Technologies, pp. 25-26, November 2004.
[5] T. Wiegand, H. Schwtarz, A. Joch, F. Kossentini, and G. J. Sullivan, “Rate-constrained coder control and comparison of video coding standards,” IEEE Transactions on Circuits and Systems for Video Technology ,Vol. 13, No. 7, pp. 688-703, July 2003.
[6] S.-Y. Lee, K.-M. Shin, and K.-D. Chung, “An object-based mode decision algorithm for multi-view video coding,” in Proceedings of IEEE International Symposium on Multimedia, pp. 74-81, December 2008.
[7] L. Shen, T. Yan, Z. Liu, Z. Zhang, P. An, and L. Yang, “Fast mode decision for multiview video coding,” in Proceedings of IEEE International Conference on Image Processing, pp. 2953-2956, 2009.
[8] ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, “Fast mode decision for B-slice,” JVT-K021, Munich, March 2004.
[9] M.E. Lukacs, “Predictive coding of multi-viewpoint images sets,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 521-524, April 1986.
[10] ISO/IEC 13818-2, AMD 3, “MPEG-2 multiview profile,” ISO/IEC JTC1/SC29/WG11, document no. N1366, September 1996.
[11] K. Muller, P.Merkle, A. Smolic, and T. Wiegand, “Multiview coding using AVC,” ISO/IEC JTC1/SC29/WG11, document no. M12945, January 2006.
[12] ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, “Joint multiview video model (JMVM) 1.0,” JVT-T209, Klagenfurt, Austria, July 2006.
[13] H. Schwarz, D. Marpe, and T. Wiegand, “Analysis of hierarchical B pictures and MCTF,” in Proceedings of IEEE International Conference on Multimedia and Exposition, pp. 1929-1932, July 2006.
[14] P. Merkle, A. Smolic, K. M‥uller, and T. Wiegand, “Efficient prediction structures for multiview video coding,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 17, No. 11, pp. 1461-1473, November 2007.
[15] L. Shen, Z. Liu, T. Yan, Z. Zhaoyang, and P. An, “Early skip mode decision for MVC using inter-view correlation,” Signal Processing: Image Communication, Vol. 25, No. 12, pp.88-93, February 2010.
[16] H. Zeng, K.-K. Ma, and C. Cai, “Mode-correlation-based early termination mode decision for multi-view video coding,” in Proceedings of IEEE International Conference on Image Processing, pp. 3405-3408, September 2010.
[17] B. Zatt, M. Shafique, S. Bampi, and J. Henkel, “An adaptive early skip mode decision scheme for multiview video coding,” in Proceedings of Picture Coding Symposium, pp. 42-45, December 2010.
[18] Z. Peng, G. Jiang, M. Yu, and Q. Dai, “Fast macroblock mode selection algorithm for multiview video coding,” EURASIP Journal Transactions on Image and Video Processing, Vol. 2008, September 2008.
[19] M. Ai, J. Wang, “A fast mode decision algorithm for multiview video codeing,” in Proceedings of IEEE International Congress on Image and Signal Processing, pp. 3252-3257, October 2010.
[20] L. Shen, Z. Liu, S. Liu, Z. Zhang, and P. An, “Selective disparity estimation and variable size motion estimation based on motion homogeneity for multi-view coding,” IEEE Transactions on Broadcasting, Vol. 55, No. 4, pp. 761-766, December 2009.
[21] W. Zhu, X. Tian, F. Zhou, and T. Chen, “Fast inter mode decision based on textural segmentation and correlations for multiview video coding,” IEEE Transactions on Consumer Electronics, Vol. 56, No. 3, pp. 1696-1704, August 2010.
[22] E. Martinez-Enriquez, M. de-Frutos-Lopez, J. C. Pujol-Alcolado, and F. Diaz-de-Maria, "A fast motion-cost based algorithm for H.264/AVC inter mode decision," in Proceedings of IEEE International Conference on Image Processing, pp.325-328, September 2007.
[23] W. Ma, S. Yang, L. Gao, C. Pei, and S. Yan, “Fast mode selection scheme for H.264/AVC inter prediction based on statistical learning method,” in Proceedings of IEEE International Conference on Multimedia and Exposition, pp.17-20, July 2009.
[24] ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, “Common test conditions for multiview video coding,” JVT-T207, Klagenfurt, Austria, July 2006.
[25] A. Vetro, M. McGuire, W. Matusik, A. Behrens, J. Lee, H. Pfister, and Mitsubishi Electric Research Labs(USA), “Multiview video test sequences from MERL,” ISO/IEC JTC1/SC29/WG11 m12077, Busan, Korea, April 2005.
[26] M. Tanimoto, T. Fujii, T. Senoh, T. Aoki, and Y. Sugihara, “Test sequences with different camera arrangements for call for proposals on multiview video coding,” ISO/IEC JTC1/SC29/WG11 m12338, Poznan, Poland, July 2005.
[27] G. Bjontegaard, “Calculation of average PSNR difference between RD-curves,” ITU-T Q6/SG16, Doc. VCEG-M33, April 2001.

指導教授

唐之瑋(Chih-Wei Tang)

審核日期

2011-7-20

推文