7786721
Geometry completion and detail generation by texture synthesis
We present a novel method for patching holes in polygonal meshes and synthesizing surfaces with details based on existing geometry. The most novel feature of our proposed method is that we transform the 3D geometry synthesis problem into a 2D domain by parameterizing surfaces and solve this problem in that domain. We then derive local geometry gradient images that encode intrinsic local geometry properties, which are invariant to object translation and rotation. The 3D geometry of holes is then reconstructed from synthesized local gradient images. This method can be extended to execute other mesh editing operations such as geometry detail transfer or synthesis. The resulting major benefits of performing geometry synthesis in 2D are more flexible and robust control, better leveraging of the wealth of current 2D image completion methods, and greater efficiency.
5893940
Multiresolution tetrahedral framework for visualizing regular volume data
The authors present a multiresolution framework, called Multi-Tetra framework, that approximates volume data with different levels-of-detail tetrahedra. The framework is generated through a recursive subdivision of the volume data and is represented by binary trees. Instead of using a certain level of the Multi-Tetra framework for approximation, an error-based model (EBM) is generated by recursively fusing a sequence of tetrahedra from different levels of the Multi-Tetra framework. The EBM significantly reduces the number of voxels required to model an object, while preserving the original topology. The approach provides continuous distribution of rendered intensity or generated isosurfaces along boundaries of different levels-of-detail thus solving the crack problem. The model supports typical rendering approaches, such as marching cubes, direct volume projection, and splatting. Experimental results demonstrate the strengths of the approach.
12895532
Volume cutout
We present a novel method for cutting out 3D volumetric structures based on simple strokes that are drawn directly on volume rendered images. The freehand strokes roughly mark out objects of interest and background. Our system then automatically segments the regions of interest and refines their boundaries in the rendered image. These 2D segmentation results provide constraints for 3D segmentation in the volume dataset. The objects of interest are then efficiently cut out from the volume via a combination of our novel two-pass graph cuts algorithm and the pre-computed over-segmentation. Our method improves traditional, fully automatic segmentation by involving human users in the process, yet minimizing user input and providing timely feedback. Our experiments show that our method extracts volumetric structures precisely and efficiently while requiring little skill or effort from the user.
53234559
Adaptive Perspective Ray Casting
7259311
Image-Based Rendering of Surfaces from Volume Data
We present an image-based rendering technique to accelerate rendering of surfaces from volume data. We cache the fully volume rendered image (called keyview) and use it to generate novel views without ray-casting every pixel. This is achieved by first constructing an underlying surface model of the volume and then texture mapping the keyview onto the geometry.When the novel view moves slightly away from the keyview, most of the original visible regions in the keyview are still visible in the novel view. Therefore, we only need to cast rays for pixels in the newly visible regions, which usually occupy only a small portion of the whole image, resulting in a substantial speedup. We have applied our technique to a virtual colonoscopy system and have obtained an interactive navigation speed through a 5123 size patient colon. Our experiments demonstrate an average of an order of magnitude speedup over that of traditional volume rendering, compromising very little on image quality.
6763688
Paint Inspired Color Mixing and Compositing for Visualization
Color is often used to convey information, and color compositing is often required while visualizing multiattribute information. This paper proposes an alternative method for color compositing. In order to present understandable color blending to the general public, several techniques are proposed. First, a paint-inspired RYB color space is used. In addition, noise patterns are employed to produce subregions of pure color within an overlapped region. We show examples to demonstrate the effectiveness of our technique for visualization
16166391
Linear k-arboricities on trees
Abstract For a fixed positive integer k, the linear k-arboricity lak(G) of a graph G is the minimum number l such that the edge set E(G) can be partitioned into l disjoint sets and that each induces a subgraph whose components are paths of lengths at most k. This paper studies linear k-arboricity from an algorithmic point of view. In particular, we present a linear-time algorithm to determine whether a tree T has lak(T)⩽m.
7426756
Content-based language models for spoken document retrieval
Spoken document retrieval (SDR) has been extensively studied in recent years because of its potential use in navigating large multimedia collections in the near future. This paper presents a novel concept of applying the content-based language models to spoken document retrieval. In an example task for retrieval of Mandarin broadcast news, the content-based language models either trained with the automatic transcriptions of the spoken documents or adapted from the baseline language models using the automatic transcriptions of the spoken documents were used to create the more accurate recognition results and indexing terms from both the spoken documents and the speech queries. We report on some interesting findings obtained in this research.
15709443
Voice retrieval of Mandarin broadcast news speech
This paper presents an improved framework for voice retrieval of Mandarin broadcast news speech. First, several unsupervised and data-driven approaches for broadcast news transcription were proposed to improve the speech recognition accuracy and efficiency. Then, a multiscale indexing paradigm for broadcast news retrieval was exploited to alleviate the problems caused by the speech recognition errors and the flexible wording structure of the Chinese language. Finally, we used the PDA as the platform and broadcast radio programs collected in Taiwan as the document collection to establish a speech-based multimedia information retrieval prototype system. Very encouraging results were obtained.
1586078
Dual photography
We present a novel photographic technique called dual photography, which exploits Helmholtz reciprocity to interchange the lights and cameras in a scene. With a video projector providing structured illumination, reciprocity permits us to generate pictures from the viewpoint of the projector, even though no camera was present at that location. The technique is completely image-based, requiring no knowledge of scene geometry or surface properties, and by its nature automatically includes all transport paths, including shadows, inter-reflections and caustics. In its simplest form, the technique can be used to take photographs without a camera; we demonstrate this by capturing a photograph using a projector and a photo-resistor. If the photo-resistor is replaced by a camera, we can produce a 4D dataset that allows for relighting with 2D incident illumination. Using an array of cameras we can produce a 6D slice of the 8D reflectance field that allows for relighting with arbitrary light fields. Since an array of cameras can operate in parallel without interference, whereas an array of light sources cannot, dual photography is fundamentally a more efficient way to capture such a 6D dataset than a system based on multiple projectors and one camera. As an example, we show how dual photography can be used to capture and relight scenes.
2577652
Bellwether analysis: predicting global aggregates from local regions
Massive datasets are becoming commonplace in a wide range of domains, and mining them is recognized as a challenging problem with great potential value. Motivated by this challenge, much effort has been concentrated on developing scalable versions of machine learning algorithms. An often overlooked issue is that large datasets are rarely labeled with the outputs that we wish to learn to predict, due to the human labor required. We make the key observation that analysts can often use queries to define labels for cases, which leads to the problem of learning to predict such query-produced labels. Of course, if a dataset is available in its entirety, we can simply run the query again to compute labels. The interesting scenarios are those where, after the predictive model is trained, new data is gathered at significant incremental cost and, perhaps, over time. The challenge is to accurately predict the query-labels for the projected completion of new datasets, based only on certain cost-effective subsets, which we call bellwethers.