Distance detection method, distance detection system and computer program product

A distance detection system for navigating a vehicle, comprising:

• a system for vehicles, comprising a processor, wherein
• the processor compares a street view image with a real-time image according to a first distance,
• the processor determines a depth distance between the vehicle and a target position from an average value of a depth map associated with the real-time image based on a comparison result of the street view image and the real-time image, wherein the target position comprises at least one coordinate, and
• the processor outputs the depth distance between the vehicle and the target position based on the depth map to prompt a user of the vehicle,
• wherein in the operation of comparing the street view image with the real-time image,
• the processor obtains a plurality of first feature points and a plurality of second feature points, wherein the plurality of first feature points are selected from the street view image corresponding to a first geographic position, and the plurality of second feature points are selected from the real-time image corresponding to the same first geographic position,
• wherein in the operation of obtaining the plurality of first feature points and the plurality of second feature points,
• the processor obtains a plurality of fourth feature points in the street view image and a plurality of fifth feature points in the real-time image;
• the processor groups the plurality of fourth feature points to obtain a plurality of first feature point groups, and selects a second feature point group with the plurality of first feature points from the plurality of first feature point groups, wherein the number of the plurality of first feature points is greater than the number of the feature points of each of the other feature point groups other than the second feature point group in the plurality of first feature point groups;
• and
• the processor groups the plurality of fifth feature points to obtain a plurality of third feature point groups, and selects a fourth feature point group with the plurality of second feature points from the plurality of third feature point groups, wherein the number of the plurality of second feature points is greater than the number of the feature points of each of the other feature point groups other than the fourth feature point group in the plurality of third feature point groups.

A computer program product, comprising a computer readable recording medium, wherein the computer readable recording medium records at least one program instruction, and the program instruction is loaded into an electronic device to execute the following steps:

• comparing a street view image with a real-time image according to a first distance;
• determining a depth distance between a vehicle and a target position from an average value of a depth map associated with the real-time image based on a comparison result of the street view image and the real-time image, wherein the target position comprises at least one coordinate;
• and
• outputting the depth distance between the vehicle and the target position based on the depth map to prompt a user of the vehicle,
• wherein the step of comparing the street view image with the real-time image comprises:
• obtaining a plurality of first feature points and a plurality of second feature points, wherein the plurality of first feature points are selected from the street view image corresponding to a first geographic position, and the plurality of second feature points are selected from the real-time image corresponding to the same first geographic position,
• wherein the step of obtaining the plurality of first feature points and the plurality of second feature points comprises:
• obtaining a plurality of fourth feature points in the street view image and a plurality of fifth feature points in the real-time image;
• grouping the plurality of fourth feature points to obtain a plurality of first feature point groups, and selecting a second feature point group with the plurality of first feature points from the plurality of first feature point groups, wherein the number of the plurality of first feature points is greater than the number of the feature points of each of the other feature point groups other than the second feature point group in the plurality of first feature point groups;
• and
• grouping the plurality of fifth feature points to obtain a plurality of third feature point groups, and selecting a fourth feature point group with the plurality of second feature points from the plurality of third feature point groups, wherein the number of the plurality of second feature points is greater than the number of the feature points of each of the other feature point groups other than the fourth feature point group in the plurality of third feature point groups.