VR portal is a powerful tool connecting multiple VR spaces and providing impressive visual effects. The implementation of VR portals requires the VR compositor to perform a clipping operation. For performance reason, the clipping needs to be performed in vertex shader, which prevents most of existing algorithm to be used here. This paper proposes a novel algorithm that performs the clipping operation with a single distance value. The proposed algorithm is well suited for the vertex shader, and can handle both normal clipping and inverse clipping. This enables users to view a VR portal from both sides. The proposed algorithm also saves the number of clip planes for other purposes, and its performance is superior to the traditional algorithm with multiple clip planes.

Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the overall network performance. Previous studies on sensor deployment mainly focused on sensor networks on 2D plane or in 3D volume. In this paper, we tackle the problem of optimal sensor deployment on 3D surfaces, aiming to achieve the highest overall sensing quality. In general, the reading of a sensor node exhibits unreliability, which often depends on the distance between the sensor and the target to be sensed, as observed in a wide range of applications. Therefore, with a given set of sensors, a sensor network offers different accuracy in data acquisition when the sensors are deployed in different ways in the Field of Interest (FoI). We formulate this optimal surface deployment problem in terms of sensing quality by introducing a general function to measure the unreliability of monitored data in the entire sensor network. We present its optimal solution and propose a series of algorithms for practical implementation. Extensive simulations are conducted on various 3D mountain surface models to demonstrate the effectiveness of the proposed algorithms.

Centroidal Voronoi tessellations (CVT) are widely used in computational science and engineering. The most commonly used method is Lloyd's method, and recently the L-BFGS method is shown to be faster than Lloyd's method for computing the CVT. However, these methods run on the CPU and are still too slow for many practical applications. We present techniques to implement these methods on the GPU for computing the CVT on 2D planes and on surfaces, and demonstrate significant speedup of these GPU-based methods over their CPU counterparts. For CVT computation on a surface, we use a geometry image stored in the GPU to represent the surface for computing the Voronoi diagram on it. In our implementation a new technique is proposed for parallel regional reduction on the GPU for evaluating integrals over Voronoi cells.

We presents a spectral approach to simulate hybrid objects with deformable and rigid materials in real time. This framework is able to handle large-scale model under the help of GPU's parallel computation.

The centroidal Voronoi tessellation (CVT) has found versatile applications in geometric modeling, computer graphics, and visualization. In this paper, we extend the concept of the CVT from Euclidean space to hyperbolic space. A novel hyperbolic CVT energy is defined, and the relationship between minimizing this energy and the hyperbolic CVT is proved. We also show by our experimental results that the hyperbolic CVT has the similar property as its Euclidean counterpart where the sites are uniformly distributed according to given density values. Two algorithms -- Lloyd's algorithm and the L-BFGS algorithm -- are adopted to compute the hyperbolic CVT, and the convergence of Lloyd's algorithm is proved. As an example of the application, we utilize the hyperbolic CVT to compute uniform partitions and high-quality remeshing results for high-genus (genus>1) surfaces.

Collaborative virtual environment has been limited on static or rigid 3D models, due to the difficulties of real-time streaming of large amounts of data that is required to describe motions of 3D deformable models. Streaming shape deformations of complex 3D models arising from a remote user's manipulations is a challenging task. In this paper, we present a framework based on spectral transformation that encodes surface deformations in a frequency format to successfully meet the challenge, and demonstrate its use in a distributed virtual environment. Our research contributions through this framework include: i) we reduce the data size to be streamed for surface deformations since we stream only the transformed spectral coefficients and not the deformed model; ii) we propose a mapping method to allow models with multi-resolutions to have the same deformations simultaneously; iii) our streaming strategy can tolerate loss without the need for special handling of packet loss. Our system guarantees real-time transmission of shape deformations and ensures the smooth motions of 3D models. Moreover, we achieve very effective performance over real Internet conditions as well as a local LAN. Experimental results show that we get low distortion and small delays even when surface deformations of large and complicated 3D models are streamed over lossy networks.

Abstract A novel framework is proposed in this paper to simulate hybrid solids with deformable and rigid materials in real‐time. Both types of materials are uniformly integrated into one spectral simulator. Based on the modal warping technique, we employ a new constraint strategy which eliminates the accumulation of approximation errors at the boundary interfaces, thus naturally gluing different materials. We also utilize the GPU to accelerate the run‐time computation when updating the geometry of the hybrid solid—the most expensive step in this framework. This work provides a general‐purpose solution of simulating hybrid objects in real‐time, even for large‐scale models. Copyright © 2010 John Wiley & Sons, Ltd.

10.1145/1342250.1342264

This paper studies jump flooding as an algorithmic paradigm in the general purpose computation with GPU. As an example application of jump flooding, the paper discusses a constant time algorithm on GPU to compute an approximation to the Voronoi diagram of a given set of seeds in a 2D grid. The errors due to the differences between the approximation and the actual Voronoi diagram are hardly noticeable to the naked eye in all our experiments. The same approach can also compute in constant time an approximation to the distance transform of a set of seeds in a 2D grid. In practice, such constant time algorithm is useful to many interactive applications involving, for example, rendering and image processing. Besides the experimental evidences, this paper also confirms quantitatively the effectiveness of jump flooding by analyzing the occurrences of errors. The analysis is a showcase of insights to the jump flooding paradigm, and may be of independent interests to other applications of jump flooding.

This paper studies the usage of the GPU as a collection of groups of related processing units, where each group communicates in some way to complete a computation efficiently and effectively. In particular, we use the GPU to perform jump flooding to pass information among groups of processing units in the design of two simple real-time soft shadow algorithms. These two algorithms are purely image-based in generating plausible soft shadows. Their computational costs depend mainly on the resolution of the shadow map or the screen. They run on an order of magnitude faster than existing comparable methods.