By Patrick A. Mikulastik, Hellward Broszio, Thorsten Thormählen, Onay Urfalioglu (auth.), Long-Wen Chang, Wen-Nung Lie (eds.)
The convention of the first IEEE Paci?c-Rim Symposium on snapshot and Video expertise (PSIVT 2006) used to be held at Hsinchu, Taiwan, Republic of China, on December 11–13, 2006. This quantity includes papers chosen for presentation at this convention. the purpose of this convention used to be to assemble theoretical advances and functional implementations contributing to, or being all for, photo and video know-how. PSIVT 2006 featured a complete application together with tutorials, keynote and invited talks, oral paper displays, and posters. We obtained 450 s- missions from 22 international locations and approved 141 papers between these (i.e., de?ning an recognition fee of 31.3%). The purpose used to be to set up PSIVT as a t- caliber sequence of symposia. judgements have been di?cult occasionally, yet we are hoping that the ?nal result's appropriate to all concerned. along with keynotes and invited talks, PSIVT 2006 o?ered seventy six oral displays and58posters,accordingtotheproperregistrationofthesepapersbythede?ned cut-off date. We deeply take pleasure in the aid of the reviewers, who generously spent their time to make sure a fantastic reviewing approach. helpful reviews have been supplied through reviewers, usually particularly precise, and so they definitely o?ered authors possibilities to enhance their paintings not just for this convention, but in addition for destiny research.
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Extra resources for Advances in Image and Video Technology: First Pacific Rim Symposium, PSIVT 2006, Hsinchu, Taiwan, December 10-13, 2006. Proceedings
For arbitrary images, the eﬀect of optimizations can be seen from Figure 5 through looking at relative positions of epipolar lines computed from diﬀerent data sets. It shows that the two optimization strategies bring positive eﬀects on reducing the inﬂuence of noise, and the coplanarity optimization performs better than the collinearity optimization. Figure 6 shows the reconstructed point cloud of the CITR-building in Auckland and Figure 7 visualizes the texture mapped surface model. The main edges of the building are reconstructed with 22 G.
A satisfactory 3D model of a pictured object requires a dense map of correspondences. The epipolar constraint (as calculated above) allows that correspondence search can be restricted to one-dimensional epipolar lines, it supports that images are at ﬁrst rectiﬁed following the method in , and that correspondence matching is then done by searching along a corresponding scan line in the rectiﬁed image. We also require a recovered base line between both camera positions to calculate a dense depth map.
The 3D tree models were represented by using a tree model database. Once the tree type was selected, the 3D tree model could be generated by the tree parameters . In this study, the tree types are selected manually. Fig. 5 demonstrates a sample procedure of tree modeling. The Generation of 3D Tree Models by the Integration of Multi-sensor Data (a) (b) Fig. 4. Vegetation detection (a) segmentation results (b) classified results (a) (b) 39 (c) Fig. 5. Tree modeling (a) watershed segmentation results (b) parameterized tree crowns (c) 3D tree models 3 Experiment Results Two test sites were selected for validation---an orchard area and a forest area.
Advances in Image and Video Technology: First Pacific Rim Symposium, PSIVT 2006, Hsinchu, Taiwan, December 10-13, 2006. Proceedings by Patrick A. Mikulastik, Hellward Broszio, Thorsten Thormählen, Onay Urfalioglu (auth.), Long-Wen Chang, Wen-Nung Lie (eds.)