In this paper we present a new method for interactive segmentation of a triangle mesh by using the concavity-sensitive harmonic field and anisotropic geodesic. The proposed method only requires a single vertex in a desired feature region, while most of existing methods need explicit information on segmentation boundary. From the user-clicked vertex, a candidate region which contains the desired feature region is defined and concavity-senstive harmonic field is constructed on the region by using appropriate boundary constraints. An initial isoline is chosen from the uniformly sampled isolines on the harmonic field and optimal points on the initial isoline are determined as interpolation points. Final segmentation boundary is then constructed by computing anisotropic geodesics passing through the interpolation points. In experimental results, we demonstrate the effectiveness of the proposed method by selecting several features in various 3D models.

Cluster computing has attracted much attention as an effective way of solving large-scale problems. However, only a few attempts have been made to explore mobile computing clusters that can be easily built using commodity smartphones and tablets. To investigate the possibility of mobile cluster-based rendering of large datasets, we developed a mobile GPU ray tracer that renders nontrivial 3D scenes with many millions of triangles at an interactive frame rate on a small-scale mobile cluster. To cope with the limited processing power and memory space, we first present an effective 3D scene representation scheme suitable for mobile GPU rendering. Then, to avoid performance impairment caused by the high latency and low bandwidth of mobile networks, we propose using a static load balancing strategy, which we found to be more appropriate for the vulnerable mobile clustering environment than a dynamic strategy. Our mobile distributed rendering system achieved a few frames per second when ray tracing 1024 × 1024 images, using only 16 low-end smartphones, for large 3D scenes, some with more than 10 million triangles. Through a conceptual demonstration, we also show that the presented rendering scheme can be effectively explored for augmenting real scene images, captured or perceived by augmented and mixed reality devices, with high quality ray-traced images.

A shape detail transfer is the process of extracting the geometric details of a source region and transferring it onto a target region. In this paper, we present a simple and effective method, called GeoStamp, for transferring shape details using a Poisson equation. First, the mean curvature field on a source region is computed by using the Laplace–Beltrami operator and is defined as the shape details of the source region. Subsequently, the source and target regions are parameterized on a common 2D domain, and a mean curvature field on the target region is interpolated by the correspondence between two regions. Finally, we solve the Poisson equation using the interpolated mean curvature field and the Laplacian matrix of the target region. Consequently, the mean curvature field of the target region is replaced with that of the source region, which results in the transfer of shape details from the source region to the target region. We demonstrate the effectiveness of our technique by showing several examples and also show that our method is quite useful for adding shape details to a surface patch filling a hole in a triangular mesh.