With the development of Multimedia and Internet techniques, massively increasing image and video data is playing a more and more important role in modern life. A variety of digital display devices are emerging constantly, which range from the traditional ones as PC, digital TV to the portable ones as cell phone, PDA and digital album. Along with the diversity of digital platform is an urgent problem to be solved, i.e. adaption of source data(image and video) to different screen resolution, which involves both changing the aspect ratio of source for diverse screens and changing the play length of video for diverse memory capacity of platforms.Without consideration about the content, most of the current image/video displaying application achieves the adaption through scaling source uniformly, which results in obvious distortion of the important foreground and degrades the users experience significantly. As result, image and video retargeting is developed for solving this problem. As content-aware technique, the key issue of retargeting is altering the solution and aspect ratio of source while avoiding the loss of information as much as possible. Most recently, retargeting techniques have become a hot topic in computer vision and been researched extensively. However, the existing approaches are insufficient to yield satisfactory results in all circumstances, and there is still room for improvement. This thesis first surveys the work on image and video retargeting systematically. Then, based on the analysis of the advantages and limitations of existing work, this thesis proposes a series of solutions for image and video retargeting. The contributions of this thesis are summarized as follows: 1. Cropping and warping are two classic strategies of retargeting, and have respective characters. This thesis proposes an image retargeting method through bringing cropping into a warping framework. Cropping is employed to reduce the influence of unimportant region and improve the performance of warping. One one hand, the proposed solution selectively discards the unimportant regions to free up more room for salient image content. On the other hand, the imaging quality of output mostly depends on the warping strategy, not the croppong, where the geometry and structure of content would be preserved better. The experiments on public data set demonstrates that this solution has both advantages of warping and cropping, which improves the quality of resulting image signi...
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