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6 CONCLUSION
In this paper, we present an automatic, recomposition
to retargeting method for stereoscopic images using
a global optimization algorithm, namely S3D-R2R.
To maximize stereo image composition, we minimize
a set of aesthetic quality errors formulated based on
two photo composition rules during the warping pro-
cess. Besides, our method can modify the depth per-
ception in 3D space. It also minimizes the changes the
vertical alignment between the left and right stereo
image pair. Compared to stereo cropping and warp-
ing, our method can better preserve the global im-
age context and able to modify depth perception for
better 3D viewing experiences. The unavoidable fea-
ture distortions are found for the large scale warping,
particularly stereoscopic images with complex/ geo-
metric structures. Moreover, the aspect ratio of the
salient objects can not be protected in our method. A
shape preservation constraint and/or object segmenta-
tion can be used to solve this problem. In the future
work, we would explore the stereoscopic video retar-
geting through recomposition.
REFERENCES
Basha, T., Moses, Y., and Avidan, S. (2011). Geometrically
consistent stereo seam carving. In IEEE International
Conference on Computer Vision (ICCV), pages 1816–
1823.
Du, S.-P., Hu, S.-M., and Martin, R. R. (2013). Chang-
ing perspective in stereoscopic images. IEEE Trans-
actions on Visualization and Computer Graphics,
19(8):1288–1297.
Grant, M., Boyd, S., and Ye, Y. (2008). Cvx: Matlab soft-
ware for disciplined convex programming.
Guthier, B., Kiess, J., Kopf, S., and Effelsberg, W. (2013).
Seam carving for stereoscopic video. In 11th IEEE
IVMSP Workshop, pages 1–4. IEEE.
Harel, J., Koch, C., and Perona, P. (2006). A saliency im-
plementation in matlab.
Islam, M. B., Lai-Kuan, W., and Chee-Onn, W. (2017).
A survey of aesthetics-driven image recomposition.
Multimedia Tools and Applications, 76(7):9517–
9542.
Islam, M. B., Lai-Kuan, W., Chee-Onn, W., and Low, K.-
L. (2015). Stereoscopic image warping for enhancing
composition aesthetics. In 2015 3rd IAPR Asian Con-
ference on Pattern Recognition (ACPR), pages 645–
649. IEEE.
Islam, M. B., Wong, L.-K., Low, K.-L., and Wong, C.-O.
(2018). Aesthetics-driven stereoscopic 3-d image re-
composition with depth adaptation. IEEE Transac-
tions on Multimedia, 20(11):2964–2979.
Islam, M. B., Wong, L.-K., Low, K.-L., and Wong, C. O.
(2019). Warping-based stereoscopic 3d video retarget-
ing with depth remapping. In 2019 IEEE Winter Con-
ference on Applications of Computer Vision (WACV),
pages 1655–1663. IEEE.
Lambooij, M. T., IJsselsteijn, W. A., and Heynderickx, I.
(2007). Visual discomfort in stereoscopic displays: a
review. In Electronic Imaging, pages 64900I–64900I.
International Society for Optics and Photonics.
Lee, K. Y., Chung, C. D., and Chuang, Y. Y. (2012). Scene
warping: Layer-based stereoscopic image resizing. In
Proceedings of the IEEE Computer Society Confer-
ence on Computer Vision and Pattern Recognition,
pages 49–56.
Li, B., Duan, L.-Y., Lin, C.-W., Huang, T., and Gao, W.
(2015). Depth-preserving warping for stereo image
retargeting. IEEE Transactions on Image Processing,
24(9):2811–2826.
Lin, S. S., Lin, C. H., Chang, S. H., and Lee, T. Y. (2014).
Object-coherence warping for stereoscopic image re-
targeting. IEEE Transactions on Circuits and Systems
for Video Technology, 24(5):759–768.
Lo, W.-Y., van Baar, J., Knaus, C., Zwicker, M., and Gross,
M. (2010). Stereoscopic 3D copy & paste.
Ma, L., Lin, W., Deng, C., and Ngan, K. N. (2012). Im-
age retargeting quality assessment: a study of subjec-
tive scores and objective metrics. IEEE Journal of
Selected Topics in Signal Processing, 6(6):626–639.
Mendiburu, B. (2012). 3D movie making: stereoscopic dig-
ital cinema from script to screen. CRC Press.
Niu, Y., Feng, W.-C., and Liu, F. (2012a). Enabling warping
on stereoscopic images. ACM Transactions on Graph-
ics (TOG), 31(6):183.
Niu, Y., Liu, F., Feng, W. C., and Jin, H. (2012b).
Aesthetics-based stereoscopic photo cropping for het-
erogeneous displays. IEEE Transactions on Multime-
dia, 14(3):783–796.
Qi, S. and Ho, J. (2013). Shift-map based stereo image
retargeting with disparity adjustment. In 11th Asian
Conference on Computer Vision (ACCV), pages 457–
469.
Tan, C.-H., Islam, M. B., Wong, L.-K., and Low, K.-
L. (2015). Semantics-preserving warping for stereo-
scopic image retargeting. In Image and Video Tech-
nology, pages 257–268. Springer.
Tong, R.-F., Zhang, Y., and Cheng, K.-L. (2013). Stere-
oPasting: interactive composition in stereoscopic im-
ages. IEEE Transactions on Visualization and Com-
puter Graphics, 19(8):1375–85.
Yan, T., He, S., Lau, R. W., and Xu, Y. (2013). Consistent
stereo image editing. In Proceedings of the 21st ACM
international conference on Multimedia, pages 677–
680. ACM.
Yoo, J. W., Yea, S., and Park, I. K. (2013). Content-Driven
Retargeting of Stereoscopic Images. IEEE Signal Pro-
cessing Letters, 20(5):519–522.
Zhang, F., Niu, Y., and Liu, F. (2013). Making stereo photo
cropping easy. In IEEE International Conference on
Multimedia and Expo (ICME), pages 1–6. IEEE.
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