CN111681190A - High-precision coordinate mapping method for panoramic video - Google Patents
High-precision coordinate mapping method for panoramic video Download PDFInfo
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- CN111681190A CN111681190A CN202010555904.6A CN202010555904A CN111681190A CN 111681190 A CN111681190 A CN 111681190A CN 202010555904 A CN202010555904 A CN 202010555904A CN 111681190 A CN111681190 A CN 111681190A
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- G06T3/00—Geometric image transformation in the plane of the image
- G06T3/40—Scaling the whole image or part thereof
- G06T3/4038—Scaling the whole image or part thereof for image mosaicing, i.e. plane images composed of plane sub-images
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- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
Abstract
The invention relates to a high-precision coordinate mapping method of a panoramic video, which comprises the following steps: respectively carrying out distortion removal processing on the plurality of rifle bolt videos to obtain distortion-removed rifle bolt videos; performing coordinate mapping on the undistorted bolt face video; splicing the distortion-removed gunlock videos to form a panoramic video; a coordinate mapping algorithm is applied to the panoramic video. According to the high-precision coordinate mapping method for the panoramic video, provided by the invention, the coordinate mapping algorithm is placed before the panoramic video is spliced, and the coordinate mapping is carried out on the distortion-removed gunlock video, so that the distortion and the coordinate mapping error caused by the splicing of the panoramic video are eliminated, and the high-precision coordinate mapping is realized on the panoramic video.
Description
Technical Field
The invention relates to the field of camera application, in particular to a high-precision coordinate mapping method for a panoramic video.
Background
In the field of camera application, splicing a gunlock camera video into a panoramic video through a splicing server is very common; in order to implement application of specific geographical location information on panoramic video, coordinate mapping is generally required. In the prior art, a coordinate mapping method selects some points on a panoramic video, and then the coordinates of the pixel points of the points are corresponding to longitude and latitude coordinates. In the prior art, due to distortion of video image data acquired by a camera and errors caused by panoramic video splicing, the problem that in the prior art, the error of a coordinate mapping method is large is caused.
Disclosure of Invention
In view of the defects of the implementation mode of the prior art, the invention provides a panoramic video high-precision coordinate mapping method, which is characterized in that a coordinate mapping algorithm is placed before the panoramic video is spliced, and coordinate mapping is carried out on a distortion-removed gunlock video, so that the distortion and the coordinate mapping errors caused by the splicing of the panoramic video are eliminated, and the high-precision coordinate mapping is realized on the panoramic video.
The technical scheme provided by the invention is as follows:
a high-precision coordinate mapping method for panoramic video, wherein the method comprises the following steps:
and respectively carrying out distortion removal processing on the plurality of rifle bolt videos to obtain distortion-removed rifle bolt videos.
Coordinate mapping is performed on the undistorted bolt face video.
And splicing the distortion-removed gunlock videos to form a panoramic video.
A coordinate mapping algorithm is applied to the panoramic video.
The panoramic video high-precision coordinate mapping method is characterized in that the plurality of bolt videos are respectively subjected to distortion removal processing to obtain distortion-removed bolt videos, and the method specifically comprises the following steps:
the bolt includes a plurality of adjacent bolts.
The bolt face is used for collecting real-time video data.
There is an overlapping region between the real-time video data collected by the adjacent bolt face.
And the acquired real-time video data is subjected to distortion removal through a distortion removal algorithm to obtain a distortion-removed gunlock video.
The undistorted bolt face video contains a plurality of.
The panoramic video high-precision coordinate mapping method specifically comprises the following steps of:
and the coordinate mapping is to correspond the pixel point coordinates on the gunlock video with the actual geographic coordinates.
The pixel point coordinates are the locations of the pixels in the undistorted bolt face video.
The actual geographic coordinates are represented by longitude, latitude.
The coordinate mapping is performed for each undistorted bolt face video.
The panoramic video high-precision coordinate mapping method is characterized in that the splicing of the undistorted gunlock videos into the panoramic video specifically comprises the following steps:
and splicing is performed through a splicing server.
And the splicing is to splice a plurality of undistorted rifle bolt videos into a panoramic video.
And the undistorted rifle bolt videos have overlapped areas, and the splicing is to eliminate the overlapped areas through an elimination algorithm so as to form a panoramic video.
The method for mapping the high-precision coordinates of the panoramic video, wherein the application of the coordinate mapping algorithm to the panoramic video, specifically comprises the following steps:
and clicking any point on the panoramic video.
And obtaining the pixel point coordinates of the point.
And calculating the longitude and latitude coordinates of the point according to the coordinate mapping algorithm.
The high-precision coordinate mapping method for the panoramic video, wherein the pixel point coordinates correspond to actual geographic coordinates, and the method specifically comprises the following steps:
and selecting a certain point on the distortion-removed gunlock video to obtain the pixel point coordinate of the point.
And mapping the selected point by using a longitude and latitude tester to obtain the longitude and latitude information of the point.
The coordinates of the pixel points of the selected points are associated with the latitude and longitude information to form a one-to-one corresponding relation, which is also called a coordinate mapping relation.
And a plurality of points are required to be selected for coordinate mapping on the distortion-removed gunlock video, and the points are called coordinate mapping reference points.
The panoramic video high-precision coordinate mapping method comprises the following steps of:
and (4) re-scaling the coordinate mapping.
And the coordinate mapping is recalculated by converting the pixel point coordinates of the undistorted gun camera video and the pixel point coordinates of the spliced panoramic video and corresponding the converted panoramic video pixel point coordinates to the actual geographic coordinates.
And the converted pixel point coordinates correspond to the actual geographic coordinates one by one.
The high-precision coordinate mapping method for the panoramic video, wherein the longitude and latitude coordinates of the point are calculated according to a coordinate mapping algorithm, and the method specifically comprises the following steps:
and taking pixel points in the panoramic video as input.
And calculating longitude and latitude coordinates corresponding to the pixel points by a coordinate mapping algorithm according to a coordinate mapping relation provided by the coordinate mapping reference point.
The invention provides a high-precision coordinate mapping method for a panoramic video, which is characterized in that a coordinate mapping algorithm is placed before the panoramic video is spliced, and coordinate mapping is carried out on a distortion-removed gunlock video, so that the distortion and the coordinate mapping errors caused by the splicing of the panoramic video are eliminated, and the high-precision coordinate mapping is realized on the panoramic video.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments are briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a high-precision coordinate mapping method for panoramic video according to a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is described in further detail below. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a flow chart of an optimal embodiment of a panoramic video high-precision coordinate mapping method, which is shown in figure 1. The method comprises the following specific steps:
step S100: and respectively carrying out distortion removal processing on the plurality of rifle bolt videos to obtain distortion-removed rifle bolt videos.
The bolt comprises a plurality of adjacent bolts, and the position of the bolt needs to be fixed in the actual installation process.
The bolt face is used for collecting real-time video data.
The videos collected by the adjacent gun cameras are videos of a certain large area covered by a plurality of gun units together.
There is an overlapping region between the real-time video data collected by the adjacent bolt face.
The real-time video data collected by the bolt face can have distortion.
The distortion refers to the geometric position error of pixel points on an image plane, so that an image object is distorted and deformed.
And the acquired real-time video data is subjected to distortion removal through a distortion removal algorithm to obtain a distortion-removed gunlock video.
The distortion removing algorithm is actually used for image restoration, specifically, the image is subjected to spatial transformation of pixel coordinates, and the gray value of a new pixel point is determined again.
The undistorted bolt face video includes all adjacent bolt face videos.
Step S200: coordinate mapping is performed on the undistorted bolt face video.
And the coordinate mapping is to correspond the pixel point coordinates on the gunlock video with the actual geographic coordinates.
The pixel point coordinates are the locations of the pixels in the undistorted bolt face video.
The actual geographic coordinates are represented by longitude, latitude.
The coordinate mapping is performed for each undistorted bolt face video.
Specifically, in the actual application process of coordinate mapping, a certain point is selected on the undistorted gunlock video, and the pixel point coordinate of the point is obtained.
More specifically, the pixel point coordinate is the first pixel point at the upper left corner of the undistorted gunlock video as the origin of coordinates, the abscissa of the pixel point of the selected point is represented by x, and the ordinate is represented by y.
And mapping the selected point by using a longitude and latitude tester to obtain the longitude and latitude information of the point.
The higher the precision of the latitude and longitude tester, the higher the accuracy of the coordinate mapping.
The latitude and longitude information is expressed in the form of latitude, minute and second.
The coordinates of the pixel points of the selected points are associated with the latitude and longitude information to form a one-to-one corresponding relation, which is also called a coordinate mapping relation.
And a plurality of points are required to be selected for coordinate mapping on the distortion-removed gunlock video, and the points are called coordinate mapping reference points.
The coordinate mapping reference point can be uniquely determined by the pixel point coordinate and the actual geographic longitude and latitude coordinate corresponding to the pixel point coordinate.
Step S300: and splicing the distortion-removed gunlock videos to form a panoramic video.
And splicing is performed through a splicing server.
And the splicing is to splice a plurality of undistorted rifle bolt videos into a panoramic video.
And the undistorted rifle bolt videos have overlapped areas, and the splicing is to eliminate the overlapped areas through an elimination algorithm so as to form a panoramic video.
When the panoramic video is spliced, the coordinate mapping needs to be converted again.
And the coordinate mapping is converted again by converting the pixel point coordinates of the undistorted gun camera video and the pixel point coordinates of the spliced panoramic video, wherein the conversion is that the first pixel point at the upper left corner of the panoramic video is taken as the origin of coordinates, and in the panoramic video, the pixel point coordinate of a certain pixel point and the coordinate of the pixel point in the original undistorted gun camera video form a corresponding relation.
And the converted pixel point coordinates of the panoramic video correspond to the actual geographic coordinates, namely correspond to the longitude and latitude.
And the converted pixel point coordinates correspond to the actual geographic coordinates one by one.
The one-to-one correspondence is referred to as a coordinate mapping relationship.
And forming a coordinate mapping reference point by a plurality of groups of coordinate mapping relations in the panoramic video.
Specifically, the pixel coordinates are stored in a pixel mapping table, and the pixel mapping table stores pixel related information.
The latitude and longitude information is stored in a GPS coordinate mapping table.
The pixel mapping table corresponds to the GPS coordinate mapping table to form a mutual conversion association relation.
Step S400: a coordinate mapping algorithm is applied to the panoramic video.
And clicking any point on the panoramic video.
And acquiring the coordinates of the pixel points of the point, namely the information of the abscissa x and the ordinate y of the point relative to the pixel points at the upper left corner of the panoramic video.
And calculating the longitude and latitude coordinates of the point according to the coordinate mapping algorithm.
Specifically, an abscissa x and an ordinate y of a certain pixel point of the panoramic video are used as input.
And calculating longitude and latitude coordinates corresponding to the pixel points by a coordinate mapping algorithm according to a coordinate mapping relation provided by the coordinate mapping reference point.
Specifically, the coordinate position in the GPS coordinate mapping table is converted according to the positions of the abscissa x and the ordinate y of the pixel point in the pixel mapping table, that is, the longitude and latitude coordinates corresponding to the pixel point.
The invention provides a high-precision coordinate mapping method for a panoramic video, which is characterized in that a coordinate mapping algorithm is placed before the panoramic video is spliced, and coordinate mapping is carried out on a distortion-removed gunlock video, so that the distortion and the coordinate mapping errors caused by the splicing of the panoramic video are eliminated, and the high-precision coordinate mapping is realized on the panoramic video.
It should be understood that the invention is not limited to the embodiments described above, but that modifications and variations can be made by one skilled in the art in light of the above teachings, and all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (8)
1. A high-precision coordinate mapping method for panoramic video is characterized by comprising the following steps:
respectively carrying out distortion removal processing on the plurality of rifle bolt videos to obtain distortion-removed rifle bolt videos;
performing coordinate mapping on the undistorted bolt face video;
splicing the distortion-removed gunlock videos to form a panoramic video;
a coordinate mapping algorithm is applied to the panoramic video.
2. The method for mapping the high-precision coordinates of the panoramic video according to claim 1, wherein the plurality of the rifle bolt videos are respectively subjected to distortion removal processing to obtain distortion-removed rifle bolt videos, and the method specifically comprises the following steps:
the bolt comprises a plurality of adjacent bolts;
the gunlock is used for acquiring real-time video data;
overlapping areas exist between the real-time video data collected by the adjacent gunlocks;
the collected real-time video data is subjected to distortion removal through a distortion removal algorithm to obtain a distortion-removed gunlock video;
the undistorted bolt face video contains a plurality of.
3. The method for high-precision coordinate mapping of panoramic video according to claim 1, wherein the coordinate mapping on the undistorted gunlock video specifically comprises:
the coordinate mapping is to correspond the pixel point coordinates on the gunlock video with the actual geographic coordinates;
the pixel point coordinates are the positions of the pixels in the undistorted rifle bolt video;
the actual geographic coordinates are represented by longitude, latitude;
the coordinate mapping is performed for each undistorted bolt face video.
4. The method for high-precision coordinate mapping of panoramic video according to claim 1, wherein the splicing of the undistorted gunlock video into the panoramic video specifically comprises:
the splicing is performed through a splicing server;
the splicing is to splice a plurality of undistorted rifle bolt videos into a panoramic video;
and the undistorted rifle bolt videos have overlapped areas, and the splicing is to eliminate the overlapped areas through an elimination algorithm so as to form a panoramic video.
5. The method for high-precision coordinate mapping of panoramic video according to claim 1, wherein the applying the coordinate mapping algorithm to the panoramic video specifically comprises:
selecting any point on the panoramic video;
acquiring the pixel point coordinates of the point;
and calculating the longitude and latitude coordinates of the point according to the coordinate mapping algorithm.
6. The method for mapping the high-precision coordinates of the panoramic video according to claims 1 and 3, wherein the coordinates of the pixel points correspond to actual geographic coordinates, and specifically comprises the following steps:
selecting a certain point on the distortion-removed gunlock video to obtain the pixel point coordinate of the point;
surveying and mapping the selected point by using a longitude and latitude tester to obtain longitude and latitude information of the point;
associating the coordinates of the pixel points of the selected points with longitude and latitude information to form a one-to-one corresponding relation, which is also called a coordinate mapping relation;
and a plurality of points are required to be selected for coordinate mapping on the distortion-removed gunlock video, and the points are called coordinate mapping reference points.
7. The method for high-precision coordinate mapping of panoramic video according to claims 1 and 4, wherein the panoramic video stitching further comprises:
rescaling the coordinate mapping;
the coordinate mapping is recalculated by converting the pixel point coordinates of the undistorted gun camera video and the pixel point coordinates of the spliced panoramic video and corresponding the converted panoramic video pixel point coordinates to the actual geographic coordinates;
and the converted pixel point coordinates correspond to the actual geographic coordinates one by one.
8. The method for high-precision coordinate mapping of panoramic video according to claims 1, 5, and 6, wherein the calculating the longitude and latitude coordinates of the point according to the coordinate mapping algorithm specifically includes:
taking pixel points in the panoramic video as input;
and calculating longitude and latitude coordinates corresponding to the pixel points by a coordinate mapping algorithm according to a coordinate mapping relation provided by the coordinate mapping reference point.
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