The present disclosure provides a method and an apparatus for binocular ranging, capable of achieving an improved accuracy of binocular ranging. The method includes: extracting features from a left image and a right image to obtain a left feature image and a right feature image; selecting a standard feature image and obtaining a cost volume of the standard feature image by applying a correlation calculation to the left feature image and the right feature image using a block matching algorithm; obtaining a confidence volume by normalizing computational costs of all disparity values in a disparity dimension for each pixel point in the cost volume; obtaining a confidence map by selecting a maximum value from confidence levels of all the disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a mask map by mapping each pixel point having a confidence level higher than a predetermined threshold in the confidence map to 1 and mapping each pixel point having a confidence level lower than or equal to the threshold in the confidence map to 0; obtaining a disparity map by calculating an argmax value for the confidence levels of all disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a target disparity map by multiplying the mask map with the disparity map; and estimating a distance based on the target disparity map.

The present disclosure provides a method and an apparatus for binocular ranging, capable of achieving an improved accuracy of binocular ranging. The method includes: extracting features from a left image and a right image to obtain a left feature image and a right feature image; selecting a standard feature image and obtaining a cost volume of the standard feature image by applying a correlation calculation to the left feature image and the right feature image using a block matching algorithm; obtaining a confidence volume by normalizing computational costs of all disparity values in a disparity dimension for each pixel point in the cost volume; obtaining a confidence map by selecting a maximum value from confidence levels of all the disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a mask map by mapping each pixel point having a confidence level higher than a predetermined threshold in the confidence map to 1 and mapping each pixel point having a confidence level lower than or equal to the threshold in the confidence map to 0; obtaining a disparity map by calculating an argmax value for the confidence levels of all disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a target disparity map by multiplying the mask map with the disparity map; and estimating a distance based on the target disparity map.

A handheld device for the image-based measurement of a remote object, comprising a housing having a front side and a rear side, a first and second camera, which are arranged having a stereo base on the rear side, for recording images of the object, an analysis unit having an algorithm for the stereophotogrammetric analysis of the images of the cameras and a display unit, which is arranged on the front side, for displaying images of the object and results of the stereophotogrammetric analysis, wherein the housing has a longitudinal axis, the stereo base is aligned diagonally relative to the longitudinal axis, and the analysis unit is designed for the purpose of taking into consideration the relative alignment of the stereo base during the stereophotogrammetric analysis.

The present disclosure provides a method and an apparatus for binocular ranging, capable of achieving an improved accuracy of binocular ranging. The method includes: extracting features from a left image and a right image to obtain a left feature image and a right feature image; selecting a standard feature image and obtaining a cost volume of the standard feature image by applying a correlation calculation to the left feature image and the right feature image using a block matching algorithm; obtaining a confidence volume by normalizing computational costs of all disparity values in a disparity dimension for each pixel point in the cost volume; obtaining a confidence map by selecting a maximum value from confidence levels of all the disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a mask map by mapping each pixel point having a confidence level higher than a predetermined threshold in the confidence map to 1 and mapping each pixel point having a confidence level lower than or equal to the threshold in the confidence map to 0; obtaining a disparity map by calculating an argmax value for the confidence levels of all disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a target disparity map by multiplying the mask map with the disparity map; and estimating a distance based on the target disparity map.

The present disclosure provides a method and an apparatus for binocular ranging, capable of achieving an improved accuracy of binocular ranging. The method includes: extracting features from a left image and a right image to obtain a left feature image and a right feature image; selecting a standard feature image and obtaining a cost volume of the standard feature image by applying a correlation calculation to the left feature image and the right feature image using a block matching algorithm; obtaining a confidence volume by normalizing computational costs of all disparity values in a disparity dimension for each pixel point in the cost volume; obtaining a confidence map by selecting a maximum value from confidence levels of all the disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a mask map by mapping each pixel point having a confidence level higher than a predetermined threshold in the confidence map to 1 and mapping each pixel point having a confidence level lower than or equal to the threshold in the confidence map to 0; obtaining a disparity map by calculating an argmax value for the confidence levels of all disparity values in the disparity dimension for each pixel point in the confidence volume; obtaining a target disparity map by multiplying the mask map with the disparity map; and estimating a distance based on the target disparity map.

Embodiments of the present invention discloses a metering adjustment method, apparatus and device and a storage medium. The method includes: acquiring brightness information of a current image frame and a previous image frame captured by a shooting apparatus of an unmanned aerial vehicle (UAV); determining whether the brightness information of the current image frame changes relative to the brightness information of the previous image frame; if so, acquiring motion state information of the shooting apparatus; and adjusting a metering mode of the shooting apparatus according to the motion state information of the shooting apparatus.

Embodiments of the present invention discloses a metering adjustment method, apparatus and device and a storage medium. The method includes: acquiring brightness information of a current image frame and a previous image frame captured by a shooting apparatus of an unmanned aerial vehicle (UAV); determining whether the brightness information of the current image frame changes relative to the brightness information of the previous image frame; if so, acquiring motion state information of the shooting apparatus; and adjusting a metering mode of the shooting apparatus according to the motion state information of the shooting apparatus.