1. A method comprising: determining a set of candidate keypoints based on a first image captured with a camera; determining, for each candidate keypoint in the set of candidate keypoints, a corresponding first similarity score, wherein the first similarity score corresponding to each candidate keypoint is determined, in part, by comparing an image patch associated with the corresponding candidate keypoint to a plurality of corresponding image sections in the first image in a region around the image patch; and selecting a first subset of the candidate keypoints, wherein the first subset comprises a predefined number of candidate keypoints with lowest similarity scores.
1. A method comprising: determining a set of candidate keypoints based on a first image captured with a camera; determining, for each candidate keypoint in the set of candidate keypoints, a corresponding first similarity score, wherein the first similarity score corresponding to each candidate keypoint is determined, in part, by comparing an image patch associated with the corresponding candidate keypoint to a plurality of corresponding image sections in the first image in a region around the image patch; and selecting a first subset of the candidate keypoints, wherein the first subset comprises a predefined number of candidate keypoints with lowest similarity scores. 10. The method of claim 1 , wherein determining the set of candidate keypoints based on the first image comprises: obtaining, from the first image, a hierarchy of images, wherein each image in the hierarchy of images has a corresponding image resolution; and determining a plurality of second subsets of candidate keypoints, wherein each second subset of candidate keypoints is associated with a distinct image in the hierarchy of images, and wherein, the set of candidate keypoints comprises the plurality of second subsets of candidate keypoints.