Compressed Coverage Masks for Path Rendering on Mobile GPUs

We present an algorithm to accelerate resolution independent curve rendering on mobile GPUs. Recent trends in graphics hardware have created a plethora of compressed texture formats specific to GPU manufacturers. However, certain implementations of platform independent path rendering require generating grayscale textures on the CPU containing the extent that each pixel is covered by the curve. In this paper, we demonstrate that generating a compressed grayscale texture prior to uploading it to the GPU creates faster rendering times in addition to the memory savings. We implement a real-time compression technique for coverage masks and compare our results against the GPU-based implementation of the highly optimized Skia rendering library. We also analyze the worst case properties of our compression algorithms. We observe up to a 2 × speed improvement over the existing GPU-based methods in addition to up to a 9:1 improvement in GPU memory gains. We demonstrate the performance on multiple mobile platforms

Improved Encoding for Compressed Textures

For the past few decades, graphics hardware has supported mapping a two dimensional image, or texture, onto a three dimensional surface to add detail during rendering. The complexity of modern applications using interactive graphics hardware have created an explosion of the amount of data needed to represent these images. In order to alleviate the amount of memory required to store and transmit textures, graphics hardware manufacturers have introduced hardware decompression units into the texturing pipeline. Textures may now be stored as compressed in memory and decoded at run-time in order to access the pixel data. In order to encode images to be used with these hardware features, many compression algorithms are run offline as a preprocessing step, often times the most time-consuming step in the asset preparation pipeline. This research presents several techniques to quickly serve compressed texture data. With the goal of interactive compression rates while maintaining compression quality, three algorithms are presented in the class of endpoint compression formats. The first uses intensity dilation to estimate compression parameters for low-frequency signal-modulated compressed textures and offers up to a 3X improvement in compression speed. The second, FasTC, shows that by estimating the final compression parameters, partition-based formats can choose an approximate partitioning and offer orders of magnitude faster encoding speed. The third, SegTC, shows additional improvement over selecting a partitioning by using a global segmentation to find the boundaries between image features. This segmentation offers an additional 2X improvement over FasTC while maintaining similar compressed quality. Also presented is a case study in using texture compression to benefit two dimensional concave path rendering. Compressing pixel coverage textures used for compositing yields both an increase in rendering speed and a decrease in storage overhead. Additionally an algorithm is presented that uses a single layer of indirection to adaptively select the block size compressed for each texture, giving a 2X increase in compression ratio for textures of mixed detail. Finally, a texture storage representation that is decoded at runtime on the GPU is presented. The decoded texture is still compressed for graphics hardware but uses 2X fewer bytes for storage and network bandwidth.Doctor of Philosoph

Lightfield Compression Using Commodity Hardware Video Codecs

A lightfield video is a series of lightfield stills, which include a number of reference views and residual data describing differences between the reference views and various viewpoints. The set of reference views or images, though different enough to provide the required basis for predicting intermediate views in the dataset, are correlated enough to approximate a traditional video stream. Additionally, reference images from a single time point may be compressed as a collage of smaller images that make up a single frame of a traditional video. Temporal correlation between reference images at successive time points is exploited, similar to standard two-dimensional video, and reference images for a given frame are tied together by virtue of being part of a same two-dimensional video frame. The sequence of reference images can be treated as frames in a video, allowing the use of non-proprietary codecs on commodity hardware at times of decoding. Thus, at runtime, a video display system relying on the lightfield system can access the original data in a time and power efficient manner using common hardware and compression techniques

GST: GPU-decodable supercompressed textures

Modern GPUs supporting compressed textures allow interactive application developers to save scarce GPU resources such as VRAM and bandwidth. Compressed textures use fixed compression ratios whose lossy representations are significantly poorer quality than traditional image compression formats such as JPEG. We present a new method in the class of supercompressed textures that provides an additional layer of compression to already compressed textures. Our texture representation is designed for endpoint compressed formats such as DXT and PVRTC and decoding on commodity GPUs. We apply our algorithm to commonly used formats by separating their representation into two parts that are processed independently and then entropy encoded. Our method preserves the CPU-GPU bandwidth during the decoding phase and exploits the parallelism of GPUs to provide up to 3X faster decode compared to prior texture supercompression algorithms. Along with the gains in decoding speed, our method maintains both the compression size and quality of current state of the art texture representations

Simulation-Based Joint Estimation of Body Deformation and Elasticity Parameters for Medical Image Analysis

Estimation of tissue stiffness is an important means of noninvasive cancer detection. Existing elasticity reconstruction methods usually depend on a dense displacement field (inferred from ultrasound or MR images) and known external forces. Many imaging modalities, however, cannot provide details within an organ and therefore cannot provide such a displacement field. Furthermore, force exertion and measurement can be difficult for some internal organs, making boundary forces another missing parameter. We propose a general method for estimating elasticity and boundary forces automatically using an iterative optimization framework, given the desired (target) output surface. During the optimization, the input model is deformed by the simulator, and an objective function based on the distance between the deformed surface and the target surface is minimized numerically. The optimization framework does not depend on a particular simulation method and is therefore suitable for different physical models. We show a positive correlation between clinical prostate cancer stage (a clinical measure of severity) and the recovered elasticity of the organ. Since the surface correspondence is established, our method also provides a non-rigid image registration, where the quality of the deformation fields is guaranteed, as they are computed using a physics-based simulation

The Virtual Pediatric Airways Workbench

The Virtual Pediatric Airways Workbench (VPAW) is a patient-centered surgical planning software system targeted to pediatric patients with airway obstruction. VPAW provides an intuitive surgical planning interface for clinicians and supports quantitative analysis regarding prospective surgeries to aid clinicians deciding on potential surgical intervention. VPAW enables a full surgical planning pipeline, including importing DICOM images, segmenting the airway, interactive 3D editing of airway geometries to express potential surgical treatment planning options, and creating input files for offline geometric analysis and computational fluid dynamics simulations for evaluation of surgical outcomes. In this paper, we describe the VPAW system and its use in one case study with a clinician to successfully describe an intended surgery outcome

Efficient Large-Scale Hybrid Fluid Simulation

State-of-the-art methods for fluid simulation, including velocitybased grid methods and smoothed particle hydrodynamics [Bridson and Müller-Fischer 2007], require a detail vs. domain size tradeoff. As a result, scenes with large spatial scales are restricted to coars