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A Video Retargeting Technique for RGB-D Camera

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Computer Vision, Imaging and Computer Graphics -- Theory and Applications (VISIGRAPP 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 458))

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Abstract

This paper presents a content aware video retargeting technique with the help of an RGB-D camera based on the detection of saliency objects. The content aware image resizing algorithm requires some energy terms to separate the main contents and the background. In this work, we use the scene depth information, gradient information, visual saliency and saliency object to create an image on the visual focus of the energy map. The experimental results show that the proposed approach performs well in terms of the resized quality.

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References

  1. Avidan, S., Shamir, A.: Seam carving for content-aware image resizing. ACM Trans. Graph. 26(3), 10 (2007)

    Article  Google Scholar 

  2. Hwang, D.S., Chien, S.Y.: Content-aware image resizing using perceptual seam carving with human attention model. In: 2008 IEEE International Conference on Multimedia and Expo, pp. 1029–1032, 23–26 April 2008

    Google Scholar 

  3. Kim, J., Kim, J., Kim, C.: Image and video retargeting using adaptive scaling function. In: Proceedings of 17th European Signal Processing Conference (2009)

    Google Scholar 

  4. Kim, J.S., Kim, J.H., Kim, C.S.: Adaptive image and video retargeting technique based on fourier analysis. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 1730–1737, June 2009

    Google Scholar 

  5. Wang, Y.S., Tai, C.L., Sorkine, O., Lee, T.Y.: Optimized scale-and-stretch for image resizing. In: SIGGRAPH Asia ’08: ACM SIGGRAPH Asia 2008 papers, pp. 1–8. ACM, New York (2008)

    Google Scholar 

  6. Fergus, R., Perona, P., Zisserman, A.: Object class recognition by unsupervised scale-invariant learning. In: Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. II-264–II-271, June 2003

    Google Scholar 

  7. Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254–1259 (1998)

    Article  Google Scholar 

  8. Gao, D., Vasconcelos, N.: Integrated learning of saliency, complex features, and object detectors from cluttered scenes. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 2, pp. 282–287, June 2005

    Google Scholar 

  9. Liu, T., Sun, J., Zheng, N. N., Tang, X., Shum, H. Y.: Learning to detect a salient object. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR ’07, pp. 1–8, June 2007

    Google Scholar 

  10. Walther, D., Koch, C.: Modeling attention to salient proto-objects. Neural Netw. 19(9), 1395–1407 (2006). Brain and Attention

    Article  MATH  Google Scholar 

  11. Hou, X., Zhang, L.: Saliency detection: A spectral residual approach. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR ’07, pp. 1–8, June 2007

    Google Scholar 

  12. Rubinstein, M., Shamir, A., Avidan, S.: Improved seam carving for video retargeting. ACM Trans. Graph. 27(3), 1–9 (2008)

    Article  Google Scholar 

  13. Wang, L., Jin, H., Yang, R., Gong, M.: Stereoscopic inpainting: Joint color and depth completion from stereo images, pp. 1–8, June 2008

    Google Scholar 

  14. Achanta, R., Hemami, S., Estrada, F., Susstrunk, S.: Frequency-tuned salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 1597–1604, June 2009

    Google Scholar 

  15. Goferman, S., Zelnik-Manor, L., Tal, A.: Context-aware saliency detection. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2376–2383, June 2010

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Chung Cheng University, Chiayi, 621, Taiwan

    Huei-Yung Lin & Jhih-Yong Huang

  2. Department of Computer Science and Information Engineering, National United University, Miaoli, 360, Taiwan

    Chin-Chen Chang

Authors
  1. Huei-Yung Lin
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  2. Chin-Chen Chang
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  3. Jhih-Yong Huang
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Corresponding author

Correspondence to Huei-Yung Lin .

Editor information

Editors and Affiliations

  1. Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Inria/ZIRST, Saint Ismier, France

    Sabine Coquillart

  3. Swansea University, Swansea, United Kingdom

    Robert S. Laramee

  4. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  5. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

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© 2014 Springer-Verlag Berlin Heidelberg

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Lin, HY., Chang, CC., Huang, JY. (2014). A Video Retargeting Technique for RGB-D Camera. In: Battiato, S., Coquillart, S., Laramee, R., Kerren, A., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics -- Theory and Applications. VISIGRAPP 2013. Communications in Computer and Information Science, vol 458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44911-0_8

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  • DOI: https://doi.org/10.1007/978-3-662-44911-0_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44910-3

  • Online ISBN: 978-3-662-44911-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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