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Fast accurate contours for 3D shape recognition | IEEE Conference Publication | IEEE Xplore

Fast accurate contours for 3D shape recognition


Abstract:

We describe an efficient GPU algorithm which extracts multiple contours from an image. The algorithm uses crack codes to generate contours which sit logically between adj...Show More

Abstract:

We describe an efficient GPU algorithm which extracts multiple contours from an image. The algorithm uses crack codes to generate contours which sit logically between adjacent image values; it works scan line by scan line and it can generate multiple contours in parallel with an image streamed directly from a camera. Whilst specifically targeted at detecting object contours in stereo disparity maps, it can also be used for general segmentation with a trivial change to the code generating the crack code masks. Using a480 ALU 1.4 GHz nVidia GPU, it can generate ~ 25000 contours from a real 2048 × 768 resolution 128 level disparity map image in ~ 29 ms if the contours are further processed in the GPU (additional ~5 ms to calculate shape moments) or ~ 39 ms if contours are transferred to the host. This is ~ 40 times faster than an OpenCV CPU implementation.
Date of Conference: 28 June 2015 - 01 July 2015
Date Added to IEEE Xplore: 27 August 2015
ISBN Information:
Print ISSN: 1931-0587
Conference Location: Seoul, Korea (South)

References

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