Browsing by Author "Li, Guiqing"

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Articulated‐Motion‐Aware Sparse Localized Decomposition
    (© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Wang, Yupan; Li, Guiqing; Zeng, Zhichao; He, Huayun; Chen, Min and Zhang, Hao (Richard)
    Compactly representing time‐varying geometries is an important issue in dynamic geometry processing. This paper proposes a framework of sparse localized decomposition for given animated meshes by analyzing the variation of edge lengths and dihedral angles (LAs) of the meshes. It first computes the length and dihedral angle of each edge for poses and then evaluates the difference (residuals) between the LAs of an arbitrary pose and their counterparts in a reference one. Performing sparse localized decomposition on the residuals yields a set of components which can perfectly capture local motion of articulations. It supports intuitive articulation motion editing through manipulating the blending coefficients of these components. To robustly reconstruct poses from altered LAs, we devise a connection‐map‐based algorithm which consists of two steps of linear optimization. A variety of experiments show that our decomposition is truly localized with respect to rotational motions and outperforms state‐of‐the‐art approaches in precisely capturing local articulated motion.Compactly representing time‐varying geometries is an important issue in dynamic geometry processing. This paper proposes a framework of sparse localized decomposition for given animated meshes by analysing the variation of edge lengths and dihedral angles (LAs) of the meshes. It first computes the length and dihedral angle of each edge for poses and then evaluates the difference (residuals) between the LAs of an arbitrary pose and their counterparts in a reference one. Performing sparse localized decomposition on the residuals yields a set of components which can perfectly capture local motion of articulations.
  • Thumbnail Image
    Item
    GPU-Driven Real-Time Mesh Contour Vectorization
    (The Eurographics Association, 2022) Jiang, Wangziwei; Li, Guiqing; Nie, Yongwei; Xian, Chuhua; Ghosh, Abhijeet; Wei, Li-Yi
    Rendering contours of 3D meshes has a wide range of applications. Previous CPU-based contour rendering algorithms support advanced stylized effects but cannot achieve realtime performance. On the other hand, real-time algorithms based on GPU have to sacrifice some advanced stylization effects due to the difficulty of linking contour elements into stroke curves. This paper proposes a GPU-based mesh contour rendering method which includes the following steps: (1) before rendering, a preprocessing step analyzes the adjacency and geometric information from the 3d mesh model; (2) at runtime, an extraction stage firstly selects contour edges from the 3D mesh model, then the parallelized Bresenham algorithm rasterizes the contour edges into a set of oriented contour pixels; (3) next, Potrace is parallelized to extract (pixel) edge loops from the contour pixels; (4) subsequently, a novel segmentation procedure is designed to partition the edge loops into strokes; (5) finally, these strokes are then converted into 2D strip meshes in order to support rendering with controllable styles. Except the preprocessing step, all other procedures are implemented in parallel on a GPU. This enables our framework to achieve real-time performance for high-resolution rendering of dense mesh models.