The
San Diego
Vision Benchmark Suite
August 18, 2013

Thank you for your interest in the San Diego Vision Benchmark Suite, brought to you by Taylor's Bespoke Silicon Group (now at UW)!

Click here for the new CortexSuite, the largest vision and brain benchmark suite for computer architects in existence!


    Download SD-VBS (Version 1.4CS )    

(Note: If you are trying to download from China, and are having problems with the above link, it is because of the Great Firewall of China. Email me below to get a copy.)

The San Diego Vision Benchmark Suite (SD-VBS) is a suite of diverse vision applications drawn from the vision domain. It is intended to help architects, compiler writers, and system designers study the construction of future systems that excel at vision-oriented applications. Additionally, vision codes tend to have a fair amount of parallelism, which makes them a good candidate for formulating future multicore and parallel architectures.

The applications are drawn from the current state-of-the-art in computer vision, in consultation with vision researchers. Each benchmark is provided in both MATLAB and C form.

MATLAB is the preferred language of vision researchers, while C makes it easier to map the applications to research platforms. The C code minimizes pointer usage and employs clean constructs to make them easier for parallelization.

Furthermore, we provide a spectrum of input sets that enable researchers to control simulation time, and to understand properties as inputs increase to leverage better processor performance.

The benchmarks are listed below:

Disparity Map Motion, Tracking and Stereo Vision
Feature Tracking Motion, Tracking and Stereo Vision
Image Segmentation Image Analysis
Scale Invariant Feature Transform (SIFT) Image Analysis
Maximally Stable Regions (MSER) Image Analysis
Robot Localization Image Understanding
Support Vector Machines (SVM) Image Understanding
Image Stitch Image Processing and Formation
Texture Synthesis Image Processing and Formation



E-mail Prof. Michael B. Taylor ( ) for questions.

You can learn more about Michael Taylor's UC San Diego research in manycore architecture,
vision processors, and parallel software engineering tools for multicore here.

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