| CPC G06T 7/73 (2017.01) [G06T 7/13 (2017.01); G06T 7/136 (2017.01); G06T 2207/20164 (2013.01)] | 20 Claims |
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1. A computer-implemented visual positioning method for a mobile machine having a camera, comprising:
extracting a plurality of corner feature points corresponding to a current image captured through the camera;
determining whether a distance between each pair of the plurality of corner feature points is less than a first preset threshold;
determining whether a grayscale value of each of the plurality of corner feature points with the distance less than the first preset threshold is within a second preset threshold range, in response to the distance between each pair of the plurality of corner feature points being less than the first preset threshold;
obtaining one or more cluster sets of the corner feature points, in response to the grayscale value of the corner feature point with the distance less than the first preset threshold being within the second preset threshold range;
screening a plurality of valid feature points from the one or more cluster sets, wherein the valid feature points are evenly distributed corner feature points with an interval of a specified amount of pixels to each other in the same cluster set;
determining a positioning reliability based on a ratio of an amount of the valid feature points to an amount of the plurality of corner feature points; and
performing a visual positioning on the mobile machine based on the positioning reliability, in response to the positioning reliability being within a preset range;
wherein the obtaining the one or more cluster sets of the corner feature points comprises:
selecting a first feature point as a cluster center, wherein the first feature point is any of the corner feature points with the distance less than the first preset threshold;
calculating a grayscale mean within a predetermined area with a first pixel pitch from the cluster center;
determining whether there are adjacent feature points within a distance range of a second pixel pitch from the cluster center, wherein the second pixel pitch is larger than the first pixel pitch, and the second pixel pitch is less than or equal to the first preset threshold;
calculating a pixel deviation between the adjacent feature point and the grayscale mean, in response to there being adjacent feature points within the distance range of the second pixel pitch from the cluster center;
screening a designated adjacent feature point belonging to the same cluster set with the first feature point based on the pixel deviation; and
obtaining the one or more cluster sets of the corner feature points by performing a cluster analysis on all the corner feature points according to a clustering process with the first feature point as the cluster center.
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