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.
Fast accurate contours for 3D shape recognition
2015-06-01
1007599 byte
Conference paper
Electronic Resource
English
Fast, accurate and convergent tangent estimation on digital contours
British Library Online Contents | 2007
|Gait recognition based on shape and motion analysis of silhouette contours
British Library Online Contents | 2013
|Fast Active Contours for Sampling
IEEE | 2006
|Accurate Object Recognition with Shape Masks
British Library Online Contents | 2012
|Multi-Reference Shape Priors for Active Contours
British Library Online Contents | 2009
|