By Guangyu Zhu, Shuicheng Yan, Tony X. Han, Changsheng Xu (auth.), Kuo-Tien Lee, Wen-Hsiang Tsai, Hong-Yuan Mark Liao, Tsuhan Chen, Jun-Wei Hsieh, Chien-Cheng Tseng (eds.)
This two-volume lawsuits constitutes the refereed papers of the seventeenth foreign Multimedia Modeling convention, MMM 2011, held in Taipei, Taiwan, in January 2011. The fifty one revised usual papers, 25 targeted consultation papers, 21 poster consultation papers, and three demo consultation papers, have been conscientiously reviewed and chosen from 450 submissions. The papers are geared up in topical sections on audio, photo video processing, coding and compression; media content material looking and retrieval; multi-camera, multi-view, and 3D structures; multimedia indexing and mining; multimedia content material research; multimedia sign processing and communications; and multimedia functions. The distinctive consultation papers take care of content material research for human-centered multimedia functions; huge scale wealthy media facts administration; multimedia realizing for customer electronics; snapshot item attractiveness and compression; and interactive photo and video search.
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Extra info for Advances in Multimedia Modeling: 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part II
Even very small errors in the registration of the low-resolution frames can have negative consequences on the estimation of other super-resolution components. Within many superresolution methods, many authors consider that image registration and super-resolution image estimation as two distinct stages. However, we prefer to consider that image registration should be optimizing at the same time as recovering super-resolution, as these two stages are not truly independent, as the super-resolution problem is akin to a neural network, the components and the parameters of them are cross-connected with each other.
In order to interpret it in perspective, a brief review of super-resolution is needed. As a well-studied field, comprehensive reviews were carried out by Borman and Stevenson  in 1998 and Park  in 2003. Although there are lots of approaches to super-resolution, the formulation of this problem usually falls into either frequency or spatial domain. Historically, the earliest super-resolution methods are raised in frequency domain [4, 5, 6] as the underlying mechanism of resolution improvement, that is restoration of frequency components beyond the Nyquist limit of the individual observation image samples .
Li et al. On the Eﬀectiveness of a Retargeting Method To measure the eﬀectiveness is an important issue to design a good retargeting method. This is closely related to how to measure the performance of a mapping function. The performance of a mapping function strongly depends on correctly choosing important regions in training data. In cases of noisy data, too complex mapping function would lead to overﬁtting like distortion of an object. To select a good model, a performance measurement of the mapping function should be provided to select the best model based on diﬀerent types of noisy or clean data.