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Volume 4 No. 1
05 March 2018

Shi-Min Hu

2018, 4(1): 1-1.   doi:10.1007/s41095-018-0114-z
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Johannes Furch, Anna Hilsmann, Peter Eisert

2018, 4(1): 3-15.   doi:10.1007/s41095-017-0089-1
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In this paper, we present a novel approach for assessing and interacting with surface tracking algorithms targeting video manipulation in post-production. As tracking inaccuracies are unavoidable, we enable the user to provide small hints to the algorithms instead of correcting erroneous results afterwards. Based on 2D mesh warp-based optical flow estimation, we visualize results and provide tools for user feedback in a consistent reference system, texture space. In this space, accurate track...

Hawraa Abbas, Yulia Hicks, David Marshall, Alexei I. Zhurov, Stephen Richmond

2018, 4(1): 17-32.   doi:10.1007/s41095-017-0097-1
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The relationship between the shape and gender of a face, with particular application to automatic gender classification, has been the subject of significant research in recent years. Determining the gender of a face, especially when dealing with unseen examples, presents a major challenge. This is especially true for certain age groups, such as teenagers, due to their rapid development at this phase of life. This study proposes a new set of facial morphological descriptors, based on 3D geodes...

Hui Zhao, Na Lei, Xuan Li, Peng Zeng, Ke Xu, Xianfeng Gu

2018, 4(1): 33-42.   doi:10.1007/s41095-017-0100-x
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Polycube construction and deformation are essential problems in computer graphics. In this paper, we present a robust, simple, efficient, and automatic algorithm to deform the meshes of arbitrary shapes into polycube form. We derive a clear relationship between a mesh and its corresponding polycube shape. Our algorithm is edge-preserving, and works on surface meshes with or without boundaries. Our algorithm outperforms previous ones with respect to speed, robustness, and efficiency. Our metho...

Takazumi Kikuchi, Yuki Endo, Yoshihiro Kanamori, Taisuke Hashimoto, Jun Mitani

2018, 4(1): 43-54.   doi:10.1007/s41095-017-0098-0
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Parsing of human images is a fundamental task for determining semantic parts such as the face, arms, and legs, as well as a hat or a dress. Recent deep-learning-based methods have achieved significant improvements, but collecting training datasets with pixel-wise annotations is labor-intensive. In this paper, we propose two solutions to cope with limited datasets. Firstly, to handle various poses, we incorporate a pose estimation network into an end-to-end human-image parsing network, in orde...

Radomír Vávra, Jiří Filip

2018, 4(1): 55-69.   doi:10.1007/s41095-017-0099-z
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BRDF continues to be used as a fundamental tool for representing material appearance in computer graphics. In this paper we present a practical adaptive method for acquisition of anisotropic BRDF, based on sparse adaptive measurement of the complete four-dimensional BRDF space by means of one-dimensional slices, which form a sparse four-dimensional structure in the BRDF space, and can be measured by continuous movements of a light source and sensor. Such a sampling approach is advantageous es...

Shiming Ge, Xin Jin, Qiting Ye, Zhao Luo, Qiang Li

2018, 4(1): 71-82.   doi:10.1007/s41095-017-0102-8
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When combining very different images which often contain complex objects and backgrounds, producing consistent compositions is a challenging problem requiring seamless image editing. In this paper, we propose a general approach, called object-aware image editing, to obtain consistency in structure, color, and texture in a unified way. Our approach improves upon previous gradient-domain composition in three ways. Firstly, we introduce an iterative optimization algorithm to minimize mism...

Maryam Khanian, Ali Sharifi Boroujerdi, Michael Breuß

2018, 4(1): 83-102.   doi:10.1007/s41095-017-0101-9
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Photometric stereo is a fundamental technique in computer vision known to produce 3D shape with high accuracy. It uses several input images of a static scene taken from one and the same camera position but under varying illumination. The vast majority of studies in this 3D reconstruction method assume orthographic projection for the camera model. In addition, they mainly use the Lambertian reflectance model as the way that light scatters at surfaces. Thus, providing reliable photometric stere...