本篇論文的主旨是根據影像內容縮放立體影像之解析度。此演算法使得立體影像經過調整解析度後，保持影像中重要物件的形狀的與立體感。大多數調整解析度方法會偵測圖像中重要區域，然後以非線性變形維持重要區域的形狀，但同時造成圖像中不重要的區域產生較大的變形。此外產生非線性變形時，如果忽略影像中物體的一致性，可能會造成物體明顯扭曲或影像立體感降低。本篇論文為了解決物體不一致形變的問題，因此提出維持物體一致性的變形方法。此方法會從立體影像中找出對映的物體，如此一來對映的物體會有一致的重要性和一致的變形量，使得左眼和右眼影像的物體，俱有相似的形狀也能保有較佳的立體感，以提升立體影像調整後的品質。本論文之實驗結果，亦以量化分析方式驗證本篇方法產生的影像比相關文獻之結果能更佳的維持物體的形狀和一致性。

This paper addresses the topic of content-aware stereoscopic image retargeting. The key to this topic is consistently adapting a stereoscopic image to fit displays with various aspect ratios and sizes while preserving the shape and disparity of visually salient content. Most methods focus on preserving salient content through nonlinear image warping in which distortions caused by warping are propagated to homogenous and low-significance regions. However, disregarding the consistency of object deformation sometimes results in apparent distortions in both the shapes and disparities of objects. An object-coherence warping scheme with an object-based significance measurement is proposed in this paper to reduce this unwanted distortion. The basic idea is utilizing information of matched objects rather than matched pixels in warping. Such information implies object correspondences in a stereoscopic image pair, which allows the generation of object significance map and the consistent preservation of objects. This strategy enables our method to consistently preserve not only the spatial shapes but also the disparities of visually salient objects, yielding a pleasing content-aware retargeting. Qualitative and quantitative analyses of various stereoscopic images show that our results are better than those generated by related methods in terms of consistency of object preservation, especially for images with structure lines and evident foreground objects.

[1]S. Avidan and A. Shamir, “Seam carving for content-aware image resizing,” ACM Trans. Graph., vol. 26, no. 3, July 2007.
[2] Y.-S. Wang, C.-L. Tai, O. Sorkine, and T.-Y. Lee, “Optimized scale¬and-stretch for image resizing,” ACM Trans. Graph., vol. 27, no. 5, pp. 118:1–118:8, December 2008.
[3] S.-S. Lin, I.-C. Yeh, C.-H. Lin, and T.-Y. Lee, “Patch-based image warping for content-aware retargeting,” IEEE Trans. Multi., vol. 15, no. 2, pp. 359–368, 2013.
[4] C.-H. Chang, C.-K. Liang, and Y.-Y. Chuang, “Content-aware dis¬play adaptation and interactive editing for stereoscopic images,” IEEE Trans. Multi., vol. 13, no. 4, pp. 589–601, aug 2011.
[5] T. Basha, Y. Moses, and S. Avidan, “Geometrically consistent stereo seam carving,” in Proceedings of IEEE International Conference on Computer Vision, 2011, pp. 1816–1823.
[6] K.-Y. Lee, C.-D. Chung, and Y.-Y. Chuang, “Scene warping: Layer-based stereoscopic image resizing,” in Proceedings of IEEE Com¬puter Vision and Pattern Recognition, 2012, pp. 49–56.
[7] A. Shamir and O. Sorkine, “Visual media retargeting,” in ACM SIGGRAPH ASIA 2009 Courses, 2009, pp. 11:1–11:13.
[8] M. Rubinstein, D. Gutierrez, O. Sorkine, and A. Shamir, “A com¬parative study of image retargeting,” ACM Trans. Graph., vol. 29, no. 6, pp. 160:1–160:10, December 2010.
[9] Y. Niu, F. Liu, W. chi Feng, and H. Jin, “Aesthetics-based stereo¬scopic photo cropping for heterogeneous displays,” IEEE Trans. Multi., vol. 14, pp. 783–796, June 2012.
[10] K. Utsugi, T. Shibahara, T. Koike, K. Takahashi, and T. Naemura, “Seam carving for stereo images,” in 3DTV-Conference: The True Vision -Capture, Transmission and Display of 3D Video (3DTV¬CON), 2010, pp. 1–4.
[11] A. Shamir and S. Avidan, “Seam carving for media retargeting,” Commun. ACM, vol. 52, no. 1, pp. 77–85, January 2009.
[12] Y. Niu, W.-C. Feng, and F. Liu, “Enabling warping on stereoscopic images,” ACM Trans. Graph., vol. 31, no. 6, pp. 183:1–183:7, nov 2012.
[13] C. Wang and A. A. Sawchuk, “Disparity manipulation for stereo images and video,” in Proceedings of SPIE, vol. 6803, 2008.
[14] M. Lang, A. Hornung, O. Wang, S. Poulakos, A. Smolic, and M. Gross, “Nonlinear disparity mapping for stereoscopic 3d,” ACM Trans. Graph., vol. 29, pp. 75:1–75:10, July 2010.
[15] S.-J. Luo, I.-C. Shen, B.-Y. Chen, W.-H. Cheng, and Y.-Y. Chuang, “Perspective-aware warping for seamless stereoscopic im¬age cloning,” ACM Trans. Graph., vol. 31, no. 6, pp. 182:1–182:8, nov 2012.
[16] F. Liu, Y. Niu, and H. Jin, “Casual stereoscopic photo authoring,” IEEE Trans. Multi., vol. 15, no. 1, pp. 129–140, 2013.
[17] S. Goferman, L. Zelnik-Manor, and A. Tal, “Context-aware saliency detection,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 10, pp. 1915–1926, oct 2012.
[18] M. Grundmann, V. Kwatra, M. Han, and I. Essa, “Efficient hier¬archical graph-based video segmentation,” in Proceedings of IEEE Computer Vision and Pattern Recognition, 2010, pp. 2141–2148.
[19] A. Mansfield, P. Gehler, L. Van Gool, and C. Rother, “Scene carving: scene consistent image retargeting,” in Proceedings of the 11th European conference on Computer vision: Part I, 2010, pp. 143–156.
[20] Y.-S. Wang, H.-C. Lin, O. Sorkine, and T.-Y. Lee, “Motion¬based video retargeting with optimized crop-and-warp,” ACM Trans. Graph., vol. 29, no. 4, pp. 90:1–90:9, 2010.
[21] M. Rubinstein, A. Shamir, and S. Avidan, “Multi-operator media retargeting,” ACM Trans. Graph., vol. 28, no. 3, pp. 23:1–23:11, July 2009.