CPC G06V 10/751 (2022.01) [G06F 18/214 (2023.01); G06N 3/088 (2013.01); G06V 10/421 (2022.01); G06V 10/50 (2022.01)] | 14 Claims |
1. A computer-implemented method comprising:
receiving a first image and a second image, the first and second images depicting a same 3D surface with different camera poses;
partitioning the first image into a first group of crops;
partitioning the second image into a second group of crops;
inputting each respective crop in the first group into a machine learning model, the machine learning model outputting a first box encoding of the respective crop in the first group;
inputting each respective crop in the second group into the machine learning model, the machine learning model outputting a second box encoding of the respective crop in the second group, each of the first and second box encodings including parameters defining a box in an embedding space; and
determining an asymmetric overlap factor measuring asymmetric surface overlaps between the first image and the second image based on the first and second box encodings, the asymmetric overlap factor including an enclosure factor indicating how much surface from the first image is visible in the second image and a concentration factor indicating how much surface from the second image is visible in the first image.
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