CPC G06T 7/593 (2017.01) [G06T 7/215 (2017.01); G06T 2207/10012 (2013.01); G06T 2207/20081 (2013.01)] | 20 Claims |
1. A computer-implemented method comprising:
obtaining (i) a first plurality of feature vectors associated with a first image and (ii) a second plurality of feature vectors associated with a second image;
generating a plurality of transformed feature vectors by transforming each respective feature vector of the first plurality of feature vectors by a kernel matrix trained to define an elliptical inner product space;
generating a cost volume by determining, for each respective transformed feature vector of the plurality of transformed feature vectors, a plurality of inner products, wherein each respective inner product of the plurality of inner products is between the respective transformed feature vector and a corresponding candidate feature vector of a corresponding subset of the second plurality of feature vectors; and
determining, based on the cost volume, a pixel correspondence between the first image and the second image.
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