[show abstract][hide abstract] ABSTRACT: In this paper we present a novel method to visualize weather data with multi-layer controllable texture synthesis. Texture possesses multiple principal perceptual channels, which makes it good at encoding multiple data attributes contained in weather data. The natural textures existed in the real world especially provide plenty of choices to encode the data with visually pleasing images. A controllable texture synthesis method is developed to generate a large amount of textures which change the appearances of their individual perceptual dimensions according to the underlying distribution of data attributes. In order to encode more data attributes we further propose multi-layer texture synthesis. The background and foreground textures are separately synthesized and then combined together for display. In the end, we apply our method to some real-world weather data and demonstrate its effectiveness with a user study.
Information Visualization, 2006. IV 2006. Tenth International Conference on; 08/2006
[show abstract][hide abstract] ABSTRACT: A novel texture mapping technique is proposed based on nonlinear dimension reduction, called Bernoulli logistic embedding
(BLE). Our probabilistic embedding model builds texture mapping with minimal shearing effects. A log-likelihood function,
related to the Bregman distance, is used to measure the similarity between two related matrices defined over the spaces before
and after embedding. Low-dimensional embeddings can then be obtained through minimizing this function by a fast block relaxation
algorithm. To achieve better quality of texture mapping, the embedded results are adopted as initial values for mapping enhancement
by stretch-minimizing. Our method can be applied to both complex mesh surfaces and dense point clouds.
Journal of Computer Science and Technology 01/2006; 21:199-203. · 0.48 Impact Factor
[show abstract][hide abstract] ABSTRACT: In this paper, we present an importance-driven texture encoding algorithm based on samples. Our algorithm determines a set of samples from source texture based on combined criteria which include compression ratio, visual attention and parameterization distortion. The sample set is used to encode the majority parts of the texture. The remaining regions are then encoded by traditional compression algorithm such as vector quantization. Our method can preserve details of important areas and be extended to dynamic textures. The decoding procedure is performed entirely in programmable graphics hardware, yielding real-time frame rates. Experimental results demonstrate the efficiency and performance of our algorithm.
[show abstract][hide abstract] ABSTRACT: There are many methods based on optimization technique for resolving the problem of deformation-minimization in texture mapping. Recently, a new optimization-based method for parameterizing polygonal meshes with minimum deformation has been developed to specifically address the problem of feature matching in texture mapping. However, these optimization-based methods achieve the result of high quality at the expense of long computation time.In this paper, we present a fast analytic texture mapping method based on radial basis function (RBF) interpolation to solve the problem of constrained texture mapping. The users control the mapping process by interactively defining and editing a set of constraints consisting of 3D points picked on the surface and the corresponding 2D points of the texture. RBF is invoked to interpolate the user-defined constraints to provide an analytic parameterization of the surface. The energy-minimization characteristic of RBF also ensures that the mapping function smoothly interpolates the constraints with satisfying non-deformation properties. This method has been applied to several data sets and excellent results have been produced. Our method is much faster than the optimization-based method for texture mapping with the same good effect achieved.
[show abstract][hide abstract] ABSTRACT: Presents a new efficient texture mapping algorithm for polygonal
meshes. Texture coordinates are assigned to the vertices of the mesh
using the variational interpolation technique. For each patch to be
mapped, the algorithm first samples equidistantly the boundaries of the
patch. In order to decrease distortion, the patch is further sampled as
uniformly as possible while its texture domain are correspondingly
sampled. The variational interpolation technique is then invoked to
yield a parameterization of the patch. The experimental results
demonstrate that the algorithm has a great number of potential
applications in texture mapping and surface modeling
Computer Graphics and Applications, 2000. Proceedings. The Eighth Pacific Conference on; 02/2000
[show abstract][hide abstract] ABSTRACT: Large-scale remote sensing images, including both satellite and aerial photographs, are widely used to render terrain scenes in real-time geographic visualization systems. Such systems often require large memories in order to store fine terrain details and fast network speeds to transfer image data, if they are built as web applications. In this paper, we propose a progressive texture compression framework to reduce the memory and bandwidth cost by compressing repeated content within and among large-scale remote sensing images. Different from existing image factorization methods, our algorithm incrementally find similar regions in new images so that large-scale images can be more efficiently compressed over time. We further propose a descriptor, the Gray Split Rotate (GSR) descriptor, to accelerate the similarity search. The reconstruction quality is finally improved by compressing residual error maps using customized S3TC-like compression. Our experiment shows that even with the error maps, our system still has higher compression rate and higher compression quality than using S3TC alone, which is a typical compression solution in most existing visualization systems.