Advances in Multimedia Information Processing – PCM 2015: - download pdf or read online

By Yo-Sung Ho, Jitao Sang, Yong Man Ro, Junmo Kim, Fei Wu

ISBN-10: 3319240773

ISBN-13: 9783319240770

ISBN-10: 3319240781

ISBN-13: 9783319240787

The two-volume lawsuits LNCS 9314 and 9315, represent the court cases of the 16th Pacific-Rim convention on Multimedia, PCM 2015, held in Gwangju, South Korea, in September 2015.

The overall of 138 complete and 32 brief papers offered in those court cases used to be conscientiously reviewed and chosen from 224 submissions. The papers have been equipped in topical sections named: photo and audio processing; multimedia content material research; multimedia functions and prone; video coding and processing; multimedia illustration studying; visible knowing and popularity on substantial information; coding and reconstruction of multimedia facts with spatial-temporal details; 3D image/video processing and purposes; video/image caliber review and processing; social media computing; human motion popularity in social robotics and video surveillance; contemporary advances in image/video processing; new media illustration and transmission applied sciences for rising UHD prone.

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Read or Download Advances in Multimedia Information Processing – PCM 2015: 16th Pacific-Rim Conference on Multimedia Gwangju, South Korea, September 16–18, 2015, Proceedings, Part II PDF

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Additional resources for Advances in Multimedia Information Processing – PCM 2015: 16th Pacific-Rim Conference on Multimedia Gwangju, South Korea, September 16–18, 2015, Proceedings, Part II

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To reduce ambiguities in matching, additional information is required to formulate an accurate model. In this paper, the GCPs constraints(G) are integrated as additional regularization terms to obtain a precise disparity estimation(D) for a scene with low texture characteristics. According to Bayes rule, the posterior probability over D given G and DL is p(D|DL , G) = p(DL , G|D)p(D) p(DL , G) (1) Graph Cuts Stereo Matching Based on Patch-Match 17 where DL is the initial disparity map conducted by Patch-Match.

From formulation (4) and (5), we can obviously find that S is usually smaller than L, which is rational in reality. The new method obtains label space by propagation which is using the continuous property of neighbours’ labels. GC Settings Data Term. To measure photo-consistencies, we use a data term that was recently proposed by [18]. In the term, we use the 3D model to represent disparity. A pixels disparity di can be represented as di = ai x+bi y +ci . Therefore, the objective of finding the best disparity for each pixel is to search its disparity plane fp = (ai , bi , ci ) ∈ R3 .

The method of computing label space is divided into two steps: random selection and propagation. First, we randomly select the disparity label li of each pixel. ln ), where n is the number of pixels. Second, we optimize the initial label at each pixel, using its neighbors. k {si } (4) where k is the dimension of S and si is the optimal label for pi . si is obtained by selecting the optimal label that has the minimum ρ (through formulation (10)) compared with its 8-connected neighbors and its own last label, si = l( min {ρ(pi , pi )}) lj ∈Ni (5) where Ni is the 3 × 3 labels centred in pixel pi , pi is the projection of pi with disparity lj , l(·) is the label in Ni that has minimum ρ.

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Advances in Multimedia Information Processing – PCM 2015: 16th Pacific-Rim Conference on Multimedia Gwangju, South Korea, September 16–18, 2015, Proceedings, Part II by Yo-Sung Ho, Jitao Sang, Yong Man Ro, Junmo Kim, Fei Wu


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