By Qi Wang, Dongming Lu, Hongxin Zhang (auth.), Guoping Qiu, Kin Man Lam, Hitoshi Kiya, Xiang-Yang Xue, C.-C. Jay Kuo, Michael S. Lew (eds.)
The 2010 Pacific-Rim convention on Multimedia (PCM 2010) was once held in Shanghai at Fudan college, in the course of September 21–24, 2010. considering its inauguration in 2000, PCM has been held in a variety of areas round the Pacific Rim, specifically Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is an immense annual overseas convention geared up as a discussion board for the dissemination of state of the art technological advances and learn ends up in the fields of theoretical, experimental, and utilized multimedia research and processing. PCM 2010 featured a entire technical software which integrated seventy five oral and fifty six poster shows chosen from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the united kingdom, and america. 3 distinctive researchers, Prof. Zhi-Hua Zhou from Nanjing collage, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft learn Asia added 3 keynote talks to the convention. we're very thankful to the various those who helped to make this convention a s- cess. we wish to specially thank Hong Lu for neighborhood association, Qi Zhang for dealing with the book of the lawsuits, and Cheng Jin for taking care of the c- ference site and exposure. We thank Fei Wu for organizing the specified consultation on large-scale multimedia seek within the social community settings.
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Extra info for Advances in Multimedia Information Processing - PCM 2010: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 21-24, 2010, Proceedings, Part I
In our work, we avoid the elimination of these features by distinguishing object’s important geometric components. 3 Proposed Feature-Preserving 3D Thumbnail Generation Algorithm The proposed 3D thumbnail system aims to help the user browse multiple 3D models eﬃciently within a large 3D database. -Y. Chiang et al. Fig. 1. The proposed system framework 3D thumbnail by simplifying and approximating the original model with ﬁtting primitives. The lower resolution thumbnail requires much less hardware resource to render and can be transmitted quickly.
The performance of aﬀect estimation is measured by MAE and VAE. MAE is used to measure the average of absolute errors between estimated aﬀective scores and ground truth scores, namely M AE = 1 N N |ˆ s − s| (2) i=1 where sˆ is estimated aﬀective score, s is the ground truth label. N is the total number of test MVs. The MAE measure is widely used in prediction problem. VAE is used to measure the variation of absolute errors between estimated affective scores and ground truth scores. 02. In SVR learning, the adjusted parameters are determined by a 4-fold cross validation using a Table 3.
It enjoys simple implementation and fast computational speed. Support vector regression (SVR) is a computational learning method based on the statistical learning theory presented by Vapnik. It has been widely used in many applications such as pattern recognition and function approximations [12,13]. In our method, a nonlinear regression function is required to adequately model the data. It can be obtained by using kernels satisfying Mercer’s condition, so that original input space can be mapped into a high-dimensional dot product space.