Real-Time, GPU-Based Foreground-Background Segmentation

October 6th, 2005

Robust and accurate foreground-background segmentation is a relatively small but crucial step in several computer vision applications. It is a key element in surveillance, 3D-modelling from silhouettes, motion capture, or gesture analysis for human-computer interaction (HCI). For several of these, real-time processing is of main importance and thus should be extremely fast. This work by Andreas Griesser of ETH Zurich proposes a high-speed GPU-based implementation that processes image sequences in less than 4ms per frame and frees the CPU from this processing step altogether. Resulting segmentation exhibits compactness and smoothness in foreground areas as well as for inter-frame temporal contiguity. (Project homepage and software downloadAndreas Griesser, Computer Vision Lab, ETH Zuerich.)

An Implementation of a FIR Filter on a GPU

September 19th, 2005

Alexey Smirnov and Tzi-cker Chiueh from Stony Brook University have published a technical report describing an implementation of a FIR filter on a GPU. The results of the performance evaluation using a Geforce 6600 video card and a Pentium 4-HT 3.2 GHz-based PC indicate that the GPU implementation is better than the SSE-optimized CPU implementation for certain input parameters. (FIR on GPU project. Report: An Implementation of a FIR Filter on a GPU (warning: postscript). Technical Report, Experimental Computer Systems Lab, Stony Brook University, 2005.)

gDEBugger V2.0 Adds Performance Graph and Dashboard View

September 19th, 2005

gDEBugger, an OpenGL debugger and profiler, traces application activity on top of the OpenGL API, letting programmers see what is happening within the graphics system implementation to find bugs and optimize application performance. This major version includes two new profiling views: Performance Graph View and Performance Dashboard View. These two views contain performance counter graphs of gDEBugger, Windows and vendor-specific graphics boards (NVIDIA and 3Dlabs), including: CPU/GPU idle, graphics memory consumption, vertex and fragment processor utilization, number of API function calls per frame, amount of loaded textures and texels, frames per second, and many others. Using the gDEBugger Performance Analysis toolbar together with the new Performance views enables you to easily pinpoint graphics pipeline performance bottlenecks. (http://www.gremedy.com)

Oil Reservoir Simulation on GPUs

September 7th, 2005

Seismic Micro Technology presented GPU-based oil reservoir simulation in Madrid last month at the European Association of Geoscientists and Engineers Conference & Exhibition. The simulator was developed on dual NVIDIA GeForce GPUs using the Cg language. Grid block properties and transmissibilities are precomputed and stored in GPU textures. (“SMT thrashes Moore’s Law (July 2005)”, OilIT.com)

A Comparison of Acceleration Structures for GPU Assisted Ray Tracing

August 24th, 2005

Recently, ray tracing on consumer level graphics hardware has been introduced. So far, most published studies on this topic use the uniform grid spatial subdivision structure for reducing the number of ray/triangle intersection tests. For many types of scenes, a hierarchical acceleration structure is more appropriate. This thesis by Lars Ole Simonsen and Niels Thrane of University of Aarhus compares GPU based traversal of kd-trees and uniform grids with a novel bounding volume hierarchy traversal scheme. The three implementations are compared in terms of performance and usefulness on the GPU. The thesis concludes that on the GPU, the bounding volume hierarchy traversal technique is up to 9 times faster than its implementations of uniform grid and kd-tree. Additionally, this technique proves the simplest to implement and the most memory efficient. (Lars Ole’s Website or Direct link to thesis PDF.)

Accelerating Double-Precision FEM Simulations with GPUs

August 23rd, 2005

This paper by Dominik Göddeke, Robert Strzodka and Stefan Turek describes a preliminary algorithm to achieve double precision results by adding a CPU-based defect correction to iterative linear system solvers on the GPU. We demonstrate that identical accuracy as compared to a full CPU double precision solver is possible while still gaining a factor of 2 in speedup compared to a highly tuned cache-aware CPU reference implementation in double precision. (Accelerating Double Precision FEM Simulations with GPUs. Dominik Göddeke, Robert Strzodka and Stefan Turek. To appear in Proceedings of ASIM 2005 – 18th Symposium on Simulation Technique.)

“Hijacking the GPU”

August 23rd, 2005

This enthusiastic bit of reporting from APC Magazine provides a wild ride through the nascent field of GPGPU. (Hijacking the GPU, by Dan Warne. APC Magazine. August 11, 2005.)

The Official GPGPU FAQ (also happy birthday GPGPU.org!)

August 11th, 2005

We almost didn’t notice, but when the renewal notice for our domain arrived it pointed out that on August 1st, 2005 GPGPU.org turned 2 years old! To celebrate, we’ve added a wiki, and a few of the regulars on the forums have started The Official GPGPU FAQ. Give it a look.

Caustics Mapping: An Image-space Technique for Real-time Caustics

August 11th, 2005

Caustics are complex patterns of shimmering light formed due to reflective and refractive objects; for example, those formed on the floor of a swimming pool. Caustics Mapping is a physically based real-time caustics rendering algorithm. It utilizes the concept of backward ray-tracing, however it involves no expensive computations that are generally associated with ray-tracing and other such techniques. The main advantage of caustics mapping is that it is extremely practical for games and other interactive applications because of its high frame rates. Furthermore, the algorithm runs entirely on graphics hardware, which leaves the CPU free for other computation. There is no pre-computation involved, and therefore fully dynamic geometry, lighting, and viewing directions are supported. In addition, there is no limitation on the topology of the reciever geometry, i.e., caustics can be formed on arbitrary surfaces. (Caustics Mapping: An Image-space Technique for Real-time Caustics. Musawir A. Shah and Sumanta Pattanaik. Technical Report, School of Engineering and Computer Science, University of Central Florida, CS TR 50-07, 07/29/2005 (Submitted for Publication))

GPU Accelerated General Purpose Data Processing with MAX/MSP/Jitter

August 11th, 2005

The latest versions of Cycling ’74s MAX/MSP/Jitter software packages provide a visual programming environment for new media with applications in GPU based stream processing, real-time video processing, volume visualization, and generic n-dimensional data analysis and signal processing. Jitter supports cascaded GLSL/Cg/ARB/NV shader programs with a streamlined render-to-texture interface, allowing fast prototyping of complex shader effects to be processed in a generic data flow network. (Jitter v1.5 Upgrade Info. Cycling ’74.)

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