Kris Woodbeck's research while affiliated with University of Ottawa and other places

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Publication (1)

Figure 2: A sample of a single resonant feature, C a r , comprised of 2...
Visual cortex on the GPU: Biologically inspired classifier and feature descriptor for rapid recognition
Conference Paper
Full-text available
  • Jul 2008
We present a biologically motivated classifier and feature descriptors that are designed for execution on single instruction multi data hardware and are applied to high speed multiclass object recognition. Our feature extractor uses a cellular tuning approach to select the optimal Gabor filters to process a given input, followed by the computation...
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Citations

... Parks et al. [19] presented a CUDA implementation of a saliency system for detection and the HMAX model for recognition, both steps are 10 times faster compared with the original algorithms. Woodbeck et al. [20] presented a GPU implementation of a bio-inspired model-similar to the HMAX model-using the OpenGL framework that achieves speedups of up to three orders of magnitude. Note that these last three works are based on the HMAX model, a region-based visual feature system, which is similar to our proposed model called the AVC algorithm. ...
Reference: CUDA-based parallelization of a bio-inspired model for fast object classification
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