dc.description.abstract | In recent years, more and more image retargeting techniques have been proposed to facilitate our daily life, in particular those based on the use of seam carving, warping or the combination of them. Although these techniques are rather sophisticated, they only work for a specific pattern during retargeting. For example, these techniques can only retarget the source picture into the same shape of a square, but cannot be easily reshaped into a circular, a polygon or other shapes. This paper focuses on creating a graphics editing system, named CMAIR (Content and Mask-Aware Image Retargeting), for image retargeting, which can retarget the source images into diff erent shapes of image to highlight the salient objects of primary interest. CMAIR eff ectively supports removal of unimportant pixels, and frames as many surrounding objects inside the provided mask as possible. In this paper, we propose a unique irregular interpolation method to produce four possible target images, and an evaluation mechanism to decide the best candidate image as the final output with the consideration of image saliency. The results show that not only the source image can be placed into different targeted shapes of mask, but also the salient objects are retained and highlighted as much as possible. As a result, the salient objects become more clear in our
eyes.
Besides, a video retargeting method named BED is proposed in this study, and the proposed algorithm in this thesis focuses on maintaining the structure of straight lines and irregular shape of objects without deforming complex image contents, which may be altered in traditional seam carving of complex image or video. In addition, the proposed mechanism maintains visual continuity such that the resulting videowill not look shaky due to sudden changes in the background. Practical applicability of the proposed method was tested using both regular videos and special videos which contain vanishing lines (i.e., perspective eff ects).
Experimental results demonstrate that the proposed CMAIR can convert the rectangular image to another irregular shape of image, and all the salient objects of the targeted images are preserved. In our video results using BED, the BED approach not only resizes the video with the retention of important information, but also maintains the structural properties of objects in varios kinds of videos.
The demonstration website at http://video.minelab.tw/DETS/
EDSeamCarving/ and http://video.minelab.tw/DETS/VRDSF/ provides comparison results that illustrate the contribution of our method. | en_US |