Fast computation of generalized Voronoi diagrams using graphics hardware
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Accelerating 3D convolution using graphics hardware (case study)
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Online model reconstruction for interactive virtual environments
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Fast and simple 2D geometric proximity queries using graphics hardware
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Hardware-assisted computation of depth contours
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Ray tracing on programmable graphics hardware
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Physically-based visual simulation on graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Real-Time Consensus-Based Scene Reconstruction Using Commodity Graphics Hardware
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
A multigrid solver for boundary value problems using programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Sparse matrix solvers on the GPU: conjugate gradients and multigrid
ACM SIGGRAPH 2003 Papers
Fast image segmentation and smoothing using commodity graphics hardware
Journal of Graphics Tools - Special on hardware-accelerated rendering techniques
Real-Time image processing using graphics hardware: a performance study
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
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It is obvious that faster processors are essential for virtual reality applications. Recently, we have a new generation of graphics hardware which can enhance the reality of interactive graphics. Although it is designed for rendering purpose, its programmability is expected to be effective for other general applications. This paper evaluates its performance as an image processing unit especially for image filtering and stereo matching. First, we focus on image filtering, and compare GPU (ATI RADEON 9700 Pro) implementations to optimized CPU (Intel Pentium 4 3.06GHz) ones. Experimental results show that, for linear filtering, GPUs are from three to six times faster than CPUs. Then, we implement a block-based stereo matching algorithm using filters and depth-test-based optimization on the GPU. This implementation is shown to be twice faster than a CPU implementation. Finally, a system based on this algorithm is constructed to estimate depth from two video sequences in real time.