The need to examine and manipulate large surface models is commonly found in many science, engineering, and medical applications. On a desktop monitor, however, seeing the whole model in detail is not possible. In thi...
详细信息
We introduce a novel technique to generate painterly art maps (PAMs) for 3D nonphotorealistic rendering. Our technique can automatically transfer brushstroke textures and color changes to 3D models from samples of a p...
详细信息
Adaptively Sampled Distance Fields (ADFs) are volumetric shape representations that support a broad range of applications in the areas of computergraphics, computer vision and physics. ADFs are especially beneficial ...
详细信息
Adaptively Sampled Distance Fields (ADFs) are volumetric shape representations that support a broad range of applications in the areas of computergraphics, computer vision and physics. ADFs are especially beneficial for representing shapes with features at very diverse scales. In this paper, we propose a strategy to represent and reconstruct ADFs on modern graphics hardware (GPUs). We employ a 3D hashing scheme to store the underlying data structure and try to balance the tradeoff between memory requirements and reconstruction efficiency. To render ADFs on GPU, we use a general-purpose ray-casting technique based on sphere tracing, which guarantees the reconstruction of fine details. We also present a way to overcome the Cl discontinuities inherent to ADFs and efficiently reconstruct smooth surface normals across cell boundaries. The effectiveness of our proposal is demonstrated for isosurface rendering and morphing.
In this paper we introduce a new approach to characterizing image quality: visual equivalence, Images are visually equivalent if they convey the same information about object appearance even if they are visibly differ...
详细信息
ISBN:
(纸本)9780892082810
In this paper we introduce a new approach to characterizing image quality: visual equivalence, Images are visually equivalent if they convey the same information about object appearance even if they are visibly different. In a series of psychophysical experiments we explore how object geometry, material, and illumination interact to produce images that are visually equivalent, and we identify how two kinds of transformations on illumination fields (blurring and warping) influence observers' judgments of equivalence. We use the results of the experiments to derive metrics that can serve as visual equivalence predictors (VEPs) and we generalize these metrics so they can be applied to novel objects and scenes. Finally we validate the predictors in a confirmatory study, and show that they reliably predict observer's judgments of equivalence. Visual equivalence is a significant new approach to measuring image quality that goes beyond existing visible difference metrics by leveraging the fact that some kinds of image differences do not matter to human observers. By taking advantage of higher order aspects of visual object coding, visual equivalence metrics should enable the development of powerful new classes of image capture, compression, rendering, and display algorithms.
To overcome limitations of small screens and to provide intuitive ways of interacting with personal data, this work addresses the seamless combination of sensor-enabled phones with large displays. An intuitive basic s...
详细信息
ISBN:
(纸本)9783885792277
To overcome limitations of small screens and to provide intuitive ways of interacting with personal data, this work addresses the seamless combination of sensor-enabled phones with large displays. An intuitive basic set of tilt gestures is introduced for a stepwise or continuous interaction with both mobile applications and distant user interfaces by utilizing the handheld as a remote control. In addition, we introduce throwing gestures to transfer media documents to a large display. By means of these gestures, we also propose transferring a running interface from a mobile phone to a large screen (to improve usability) and back (to achieve mobility). We demonstrate the feasibility of the interaction methods with several application prototypes facilitating a very natural flow of interaction.
Spatial visualization skills are vital to many careers and in particular to STEM fields. Materials have been developed at Michigan Technological University and Penn State Erie, The Behrend College to assess and develo...
详细信息
Spatial visualization skills are vital to many careers and in particular to STEM fields. Materials have been developed at Michigan Technological University and Penn State Erie, The Behrend College to assess and develop spatial skills. The EnViSIONS (Enhancing Visualization Skills-Improving Options aNd Success) project is combining these materials and testing them with pre-college and college students at seven institutions: Michigan Tech, Penn State Behrend, Purdue University, University of Iowa, Virginia State University, Virginia Tech, and a "Project Lead the Way" course in south-central Arizona. By removing a barrier to success for students with low visualization skills, particularly women, the project leaders hope to improve the retention of these students in STEM disciplines and to enhance their success. This paper will give a brief overview of the implementations at the university level and the fndings.
With the explosive growth of Web and the recent development in digital media technology, the number of images on the Web has grown tremendously. Consequently, Web image clustering has emerged as an important applicati...
详细信息
ISBN:
(纸本)9781605580852
With the explosive growth of Web and the recent development in digital media technology, the number of images on the Web has grown tremendously. Consequently, Web image clustering has emerged as an important application. Some of the initial efforts along this direction revolved around clustering Web images based on the visual features of images or textual features by making use of the text surrounding the images. However, not much work has been done in using multimodal information for clustering Web images. In this paper, we propose a graph theoretical framework for simultaneously integrating visual and textual features for efficient Web image clustering. Specifically, we model visual features, images and words from surrounding text using a tripartite graph. Partitioning this graph leads to clustering of the Web images. Although, graph partitioning approach has been adopted before, the main contribution of this work lies in a new algorithm that we propose - Consistent Isoperimetric High-order Co-clustering (CIHC), for partitioning the tripartite graph. Computationally, CIHC is very quick as it requires a simple solution to a sparse system of linear equations. Our theoretical analysis and extensive experiments performed on real Web images demonstrate the performance of CIHC in terms of the quality, efficiency and scalability in partitioning the visual feature-image-word tripartite graph.
We present an adaptive dynamic load balancing scheme for 3D texture based sort-last parallel volume rendering on a PC cluster equipped with GPUs. Our scheme exploits not only task parallelism but also data parallelism...
详细信息
This paper introduces techniques for the exploration of images augmented with additional information. We present the so-called Meta-Previewer and propose the Cascading-Views which are widgets that can assist the end-u...
详细信息
In this paper we propose new methods of chemical structure classification based on the integration of graph database mining from data mining and graph kernel functions from machine learning. In our method, we first id...
详细信息
ISBN:
(纸本)9781848161085
In this paper we propose new methods of chemical structure classification based on the integration of graph database mining from data mining and graph kernel functions from machine learning. In our method, we first identify a set of general graph patterns in chemical structure data. These patterns are then used to augment a graph kernel function that calculates the pairwise similarity between molecules. The obtained similarity matrix is used as input to classify chemical compounds via a kernel machines such as the support vector machine (SVM). Our results indicate that the use of a pattern-based approach to graph similarity yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art approaches. In addition, the identification of highly discriminative patterns for activity classification provides evidence that our methods can make generalizations about a compound's function given its chemical structure. While we evaluated our methods on molecular structures, these methods are designed to operate on general graph data and hence could easily be applied to other domains in bioinformatics.
暂无评论