By Enqing Chen, Yihong Gong, Yun Tie
The two-volume court cases LNCS 9916 and 9917, represent the lawsuits of the 17th Pacific-Rim convention on Multimedia, PCM 2016, held in Xi`an, China, in September 2016.
The overall of 128 papers provided in those complaints was once rigorously reviewed and chosen from 202 submissions.
The concentration of the convention was once as follows in multimedia content material research, multimedia sign processing and communications, and multimedia functions and services.
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Chen et al. ): PCM 2016, Part II, LNCS 9917, pp. 33–42, 2016. 1007/978-3-319-48896-7 4 34 R. Bai et al. A key component of facial animation system is getting accurate facial landmarks. This problem has attracted a lot of research efforts and many detection algorithms have been proposed in recent years. These algorithms can be divided into two categories: optimization-based and regression based. Active Shape Model (ASM) [6] and Active Appearance Model (AAM) [5] reconstruct the face shape appearance by optimization approaches.
Learning depth from single monocular images. In: Advances in Neural Information Processing Systems, pp. 1161–1168 (2005) 10. : The design of high-level features for photo quality assessment. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 419–426. IEEE (2006) 11. : Content-based photo quality assessment. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 2206–2213. IEEE (2011) 12. : Assessing the aesthetic quality of photographs using generic image descriptors.
We choose 21 scenes as our initial data structure. 20 B. Zhang et al. All of them is outdoor environments with or without salient objects. For each scene, we take a background and three people in the photo with different positions and photography layouts. Moreover, one person is dressed in clothes with different colors to check the color palette effect. One person stands in different positions especially form an obvious unsightly layout. Therefore, we totally collect 630 images as our dataset. And we simply labeled non-person images as ‘background’, deliberately ugly setting images as ‘unsight’,and the remains as ‘normal’.