How to Measure the Relevance of a Retargeting Approach?
Most cell phones today can receive and display video content. Nonetheless, we are still significantly behind the point where premium made for mobile content is mainstream, largely available, and affordable. Significant issues must be overcome. The small screen size is one of them. Indeed, the direct transfer of conventional contents (i.e. not specifically shot for mobile devices) will provide a video in which the main characters or objects of interest may become indistinguishable from the rest of the scene. Therefore, it is required to retarget the content. Different solutions exist, either based on distortion of the image, on removal of redundant areas, or cropping. The most efficient ones are based on dynamic adaptation of the cropping window. They significantly improve the viewing experience by zooming in the regions of interest. Currently, there is no common agreement on how to compare different solutions. A retargeting metric is proposed in order to gauge its quality. Eye-tracking experiments, zooming effect through coverage ratio and temporal consistency are introduced and discussed.
KeywordsVideo Sequence Visual Attention Video Content Coverage Ratio Temporal Consistency
- 1.Avidan, S., Shamir, A.: eam carving for content-aware image resizing. ACM Transactions on Graphics, SIGGRAPH 26 (2007)Google Scholar
- 3.Chamaret, C., Le Meur, O.: Attention-based video reframing: validation using eye-tracking. In: ICPR (2008)Google Scholar
- 4.Chen, L., Xie, X., Fan, X., Ma, W., Zhang, H., Zhou, H.: A visual attention model for adapting images on small displays. ACM Multimedia Systems Journal 9(4) (2003)Google Scholar
- 5.Deselaers, T., Dreuw, P., Ney, H.: Pan, zoom, scan – time-coherent, trained automatic video cropping. In: IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2008)Google Scholar
- 6.Fan, X., Xie, X., Ma, W., Zhang, H., Zhou, H.: Visual attention based image browsing on mobile devices. In: ICME 2003, vol. 1, pp. 53–56 (2003)Google Scholar
- 10.Le Meur, O., Castellan, X., Le Callet, P., Barba, D.: Efficient Saliency-Based Repurposing Method. In: IEEE International Conference on Image Processing, pp. 421–424 (2006)Google Scholar
- 12.Liu, H., Xie, X., Ma, W., Zhang, H.: Automatic browsing of large pictures on mobile devices. In: ACM Multimedia Conference, pp. 148–155 (2003)Google Scholar
- 13.Kraehenbuehl, P., Manuel Lang, A.H., Gross, M.: A system for retargeting of streaming video. In: ACM Transactions on Graphics (Proc. of SIGGRAPH Asia) (2009)Google Scholar
- 15.Santella, A., Agrawala, M., Decarlo, D., Salesin, D., Cohen, M.: Gaze-based interaction for semi-automatic photo cropping. In: Proceedings of ACM’s CHI 2006, pp. 771–780 (2006)Google Scholar
- 17.Tao, C., Jia, J., Sun, H.: Active window oriented dynamic video retargeting. In: International Conference Computer Vision (2007)Google Scholar
- 19.Wolf, L., Guttmann, M., Cohen-Or, D.: Non-homogeneous content-driven video-retargeting. In: IEEE 11th International Conference on Computer Vision, ICCV 2007, pp. 1–6 (October 2007)Google Scholar
- 20.Zhang, G., Cheng, M., Hu, S., Martin, R.R.: A shape-preserving approach to image resizing. Pacific Graphics 28 (2009)Google Scholar