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Volume 3 No. 2
02 June 2017

Chao Wang,Xiaohu Guo

2017, 3(2): 95-106.   doi:10.1007/s41095-016-0072-2
Abstract ( 376 HTML ( 8   PDF(5120KB) ( 205 )   Save

In this paper we present a novel feature-based RGB-D camera pose optimization algorithm for real-time 3D reconstruction systems. During camera pose estimation, current methods in online systems suffer from fast-scanned RGB-D data, or generate inaccurate relative transformations between consecutive frames. Our approach improves current methods by utilizing matched features across all frames and is robust for RGB-D data with large shifts in consecutive frames. We directly estimate camera pose f...

Martin Bähr,Michael Breuß,Yvain Quéau,Ali Sharifi Boroujerdi,Jean-Denis Durou

2017, 3(2): 107-129.   doi:10.1007/s41095-016-0075-z
Abstract ( 384 HTML ( 1   PDF(6871KB) ( 22 )   Save

The integration of surface normals for the purpose of computing the shape of a surface in 3D space is a classic problem in computer vision. However, even nowadays it is still a challenging task to devise a method that is flexible enough to work on non-trivial computational domains with high accuracy, robustness, and computational efficiency. By uniting a classic approach for surface normal integration with modern computational techniques, we construct a solver that fulfils these requirements....

Sheng Yang,Jie Xu,Kang Chen,Hongbo Fu

2017, 3(2): 131-146.   doi:10.1007/s41095-017-0078-4
Abstract ( 306 HTML ( 1   PDF(98261KB) ( 287 )   Save

Point cloud segmentation is a fundamental problem. Due to the complexity of real-world scenes and the limitations of 3D scanners, interactive segmentation is currently the only way to cope with all kinds of point clouds. However, interactively segmenting complex and large-scale scenes is very time-consuming. In this paper, we present a novel interactive system for segmenting point cloud scenes. Our system automatically suggests a series of camera views, in which users can conveniently specify...

Yixin Zhuang,Hang Dou,Nathan Carr,Tao Ju

2017, 3(2): 147-160.   doi:10.1007/s41095-016-0071-3
Abstract ( 287 HTML ( 2   PDF(22038KB) ( 17 )   Save

We present an algorithm for segmenting a mesh into patches whose boundaries are aligned with prominent ridge and valley lines of the shape. Our key insight is that this problem can be formulated as correlation clustering (CC), a graph partitioning problem originating from the data mining community. The formulation lends two unique advantages to our method over existing segmentation methods. First, since CC is non-parametric, our method has few parameters to tune. Second, as CC is gover...

Yuxin Ma,Wei Chen,Xiaohong Ma,Jiayi Xu,Xinxin Huang,Ross Maciejewski,Anthony K. H. Tung

2017, 3(2): 161-175.   doi:10.1007/s41095-017-0077-5
Abstract ( 341 HTML ( 1   PDF(6382KB) ( 164 )   Save

Support vector machines (SVMs) are supervised learning models traditionally employed for classification and regression analysis. In classification analysis, a set of training data is chosen, and each instance in the training data is assigned a categorical class. An SVM then constructs a model based on a separating plane that maximizes the margin between different classes. Despite being one of the most popular classification models because of its strong performance empirically, understanding t...

Hui-Chi Tsai,Ya-Hsuan Lee,Ruen-Rone Lee,Hung-Kuo Chu

2017, 3(2): 177-188.   doi:10.1007/s41095-016-0076-y
Abstract ( 307 HTML ( 0   PDF(18653KB) ( 15 )   Save

Line drawing is a style of image abstraction where the perceptual content of the image is conveyed using distinct straight or curved lines. However, extracting semantically salient lines is not trivial and mastered only by skilled artists. While many parametric filters have successfully extracted accurate and coherent lines, their results are sensitive to parameter choice and easily lead to either an excessive or insufficient number of lines. In this work, we present an interactive system to ...

Yoshikatsu Nakajima,Hideo Saito

2017, 3(2): 189-198.   doi:10.1007/s41095-016-0067-z
Abstract ( 432 HTML ( 0   PDF(3811KB) ( 262 )   Save

Camera pose estimation with respect to target scenes is an important technology for superimposing virtual information in augmented reality (AR). However, it is difficult to estimate the camera pose for all possible view angles because feature descriptors such as SIFT are not completely invariant from every perspective. We propose a novel method of robust camera pose estimation using multiple feature descriptor databases generated for each partitioned viewpoint, in which the feature descriptor...