System and method for sift implementation and optimization
AssigneeIntel Corporation
InventorYurong Chen
Life of this patent
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Abstract
A method is to implement a Scale Invariant Feature Transform algorithm in a shared memory multiprocessing system. The method comprises building differences of Gaussian (DoG) images for an input image, detecting keypoints in the DoG images; assigning orientations to the keypoints and computing keypoints descriptors and performing matrix operations. In the method, building differences of Gaussian (DoG) images for an input image and detecting keypoints in the DoG images are executed for all scales of the input image in parallel. And, orientation assignment and keypoints descriptions computation are executed for all octaves of the input image in paralle.
Claims22
A system, comprising:
- a memory;
- two or more cores that shares the memory, wherein at least two cores each perform at least a thread of a scale invariant feature transform algorithm in parallel.
A method to implement a scale invariant feature transform algorithm, comprising:
- building difference of Gaussian images for all scales of an input image in parallel;
- detecting keypoints with a local extrema in the difference of Gaussian images for all scales in parallel;
- assigning orientations to the keypoints;
- and
- computing feature descriptors for the keypoints.
A machine readable medium comprising a plurality of instructions that in response to being executed result in a computing device
- building difference of Gaussian images for all scales of an input image in parallel;
- detecting keypoints with a local extrema in the difference of Gaussian images for all scales in parallel;
- assigning orientations to the keypoints;
- and
- computing feature descriptors for the keypoints.
Dependencies are inferred from the claim text.