By Deepak Ghimire, Joonwhoan Lee (auth.), Yo-Sung Ho (eds.)
The two-volume lawsuits LNCS 7087 + LNCS 7088 represent the court cases of the fifth Pacific Rim Symposium on snapshot and Video know-how, PSIVT 2011, held in Gwangju, Korea, in November 2011. the complete of seventy one revised papers used to be rigorously reviewed and chosen from 168 submissions. the subjects coated are: image/video coding and transmission; image/video processing and research; imaging and pix and visualization; image/video retrieval and scene realizing; biomedical picture processing and research; biometrics and snapshot forensics; and laptop imaginative and prescient applications.
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Additional info for Advances in Image and Video Technology: 5th Pacific Rim Symposium, PSIVT 2011, Gwangju, South Korea, November 20-23, 2011, Proceedings, Part I
The cost map Sˆmin , shown in 1/10 scale in (b), was used for the depth-reliabilitybased regularization mentioned later. When the global optimization was turned oﬀ by setting λ1 , λ2 = 0, the resulting depth map was very noisy, as shown in (c). Unless the occlusions were handled properly, depth estimation was erroneous around the occlusion boundaries, as shown in (d). When the block matching was disabled by setting the block size to 1×1 pixels, the depth map became granular, as shown in (e). When depth reﬁnement was skipped, the depth map took only the quantized values, as shown in (f).
The physical depth value for D(p) can be written as zD(p) . Second, the photometric consistency in Eq. (1) should be given over the coordinate system of the target viewpoint. Consequently, we have to map the pixels from the target viewpoint to the input viewpoints in evaluating the consistencies. Speciﬁcally, we deﬁne C(p, D(p)) as ⎧ ⎫ ⎨ ⎬ 1 C(p, D(p)) = Cm,m (q, D(q)) , (5) ⎩ ⎭ Z q∈Bp m=m where Bp is a window centered at p, m and m are the indices of input images, and Z is a constant for normalization.
Although numerous techniques have been developed for surface fairing and mesh regularization [20,22,23,24,25,26] based on heat diﬀusion. Most diﬀusion smoothing approaches mainly use ﬁnite element or ﬁnite diﬀerence schemes which is known to suﬀer numerical instability if the forward Euler scheme is used. In this paper, we propose a new smoothing framework that constructs the heat kernel analytically using the eigenfunctions of the Laplace-Beltrami operator. Although solving the eigenfunctions of the Laplace-Beltrami operator requires the ﬁnite element method, the proposed method is analytic in a sense that heat kernel smoothing is formulated as a series expansion explicitly.
Advances in Image and Video Technology: 5th Pacific Rim Symposium, PSIVT 2011, Gwangju, South Korea, November 20-23, 2011, Proceedings, Part I by Deepak Ghimire, Joonwhoan Lee (auth.), Yo-Sung Ho (eds.)