CN110211220A - The image calibration suture of panorama fish eye camera and depth reconstruction method and its system - Google Patents
The image calibration suture of panorama fish eye camera and depth reconstruction method and its system Download PDFInfo
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- CN110211220A CN110211220A CN201910342455.4A CN201910342455A CN110211220A CN 110211220 A CN110211220 A CN 110211220A CN 201910342455 A CN201910342455 A CN 201910342455A CN 110211220 A CN110211220 A CN 110211220A
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Abstract
The invention discloses the suture of the image calibration of panorama fish eye camera and depth reconstruction method and its systems, find object space, carry out creation panoramic optical object space；It is shot using panoramic picture of the panorama fisheye camera to panoramic optical object space；Create the inner parameter calibrating patterns of panorama fish eye camera；Create the image mosaic parameter model of panoramic picture and panoramic optical object space；Establish the spatial depth transformation parameter model of panoramic picture and panoramic optical object space；Simplified 3D depth algorithm can be implanted into, it is executed on single-chip microcontroller, therefore the image calibration system of fish eye camera can be calibrated immediately, easy to carry, in addition, by the required production calibration process of simplification and save the time, and while panorama fisheye camera shoots target, object space is scanned using three-dimensional laser scanner, generates three-dimensional image, calibration is compared with above-mentioned 3D panoramic image, it is further provided the authenticity of image.
Description
Technical field
The invention belongs to 3D panoramic photographing technique fields, and in particular to the image calibration of panorama fish eye camera sutures and depth
Spend method for reconstructing and its system.
Background technique
When creating camera in the world, people begin through important in image recording their daily life or history
Event.For camera work and equipment, low definition black white image has evolved to high clear colorful image and high-speed camera, can
To shift to an earlier date 2,000,000,000 frames of shooting per second.In addition, the visual effect about photography, with camera plane image but also can not only shoot
3D rendering.
In the prior art, by shooting 3D rendering using the twin-lens camera of 3D camera, but 3D rendering can be one
It is shot in a little visual angles, these visual angles are limited by equipment camera coverage or the panoramic picture of 360 degree of surroundings is by holding camera
And the photographer's shooting turned round.However, photographer, which must take a significant amount of time, carrys out photographing panorama picture with this method, because
This, the method for shooting 3D panoramic picture using multiple 3D cameras, matching there are three video cameras to tens video cameras now
It sets, but they belong to monocular vision system, because the photo range overlapping of camera is less, and by that cannot be counted using parallax
It calculates or obtains depth information, and virtual reality and the 3D information of augmented reality need depth information.Therefore, how by using phase
It is extremely important that machine obtains 3D depth information.
Summary of the invention
The purpose of the present invention is to provide the suture of the image calibration of panorama fish eye camera and depth reconstruction method and its it is
System, it is less with the photo range overlapping for solving camera mentioned above in the background art, and by that cannot be calculated using parallax
Or depth information is obtained, and the problem of virtual reality and the 3D information of augmented reality need depth information.
To achieve the above object, present invention employs following technical solutions: the image calibration of panorama fish eye camera, suture
With depth reconstruction method, include the following steps:
S100: finding object space, carries out creation panoramic optical object space；
S120: it is shot using panoramic picture of the panorama fish eye camera to the panoramic optical object space；
S130: the inner parameter calibrating patterns of creation panorama fish eye camera；
S140: the image mosaic parameter model of creation panoramic picture and the panoramic optical object space；
S150: the spatial depth transformation parameter model of panoramic picture and the panoramic optical object space is established；
S160: image mosaic parameter model is utilized, the depth conversion parameter model in space and the calibrating die of inner parameter are made
Type generates 3D panoramic picture comprising panorama depth information；
S170: being scanned object space using three-dimensional laser scanner, makes the 3-D image of scanning and the 3D of generation
Panoramic image is compared, and calibrates to 3D panoramic image.
Preferably, described image splicing parameter model includes Optimal Parameters, acquires inner parameter calibrating patterns, described image
Splice parameter model and spatial depth, the transformation parameter model from each panorama fish eye camera.
Preferably, the Optimal Parameters splice parameter model and sky for optimizing inner parameter calibrating patterns, described image
Between depth by means of the transformation parameter model of machine learning, wherein algorithm used in machine learning includes support vector machines.
Preferably, the Optimal Parameters are for updating inner parameter calibrating patterns, described image splicing parameter model and sky
Between depth conversion parameter model.
The image calibration of panorama fish eye camera, suture and depth reconstruction system, including the panorama fish eye camera and
Three-dimensional laser scanner, the panorama fish eye camera include four fish eye lenses, four cmos sensor modules and panorama sketch
Picture and panorama depth information module, wherein the angle of cut of the adjacent fish-eye shooting direction is 90 degree；The panoramic picture
The inner parameter calibrating patterns for including inner parameter calibration module and being stored therein with panorama depth information module, wherein institute
Inner parameter calibration module is stated for providing the required parameter of the coordinate transformation model between coordinate transformation model；The CMOS is passed
Sensor module includes image mosaic module and the described image being stored therein splicing parameter model, spatial depth transformation parameter mould
Block and the spatial depth transformation parameter model being stored therein, wherein described image splicing module is used for the panorama flake
The Panorama Mosaic of video camera shooting is used at panoramic pictures, the spatial depth transformation parameter module in the panorama flake
Transformation model in 2D flat image and 3d space between Object Depth is provided in video camera, obtains panorama depth information；Panorama
Each pixel and computing module in image with for generating the panoramic picture and panorama depth information module is electrically connected,
In, the pixel and computing module are for calibration and spliced panoramic picture and panorama depth information, to generate 3D panoramic picture.
Preferably, the computing module further includes optimization module, is electrically connected with the optimization module, for generating panorama sketch
Picture and panorama depth information, wherein the optimization module can accumulate supplemental characteristic by imaging from each panorama flake
Machine collects inner parameter calibrating patterns, and described image splices parameter model and spatial depth transformation parameter model, then passes through machine
Device learning method Optimal Parameters data.
Preferably, algorithm used in the machine learning includes support vector machines.
Preferably, the inner parameter calibration module, described image splicing module and the spatial depth transformation parameter mould
Block is integrated into one single chip or can be one single chip.
Technical effect and advantage of the invention: the image calibration suture of panorama fish eye camera proposed by the present invention and depth
Method for reconstructing and its system have the advantage that compared with prior art
The present invention can be with quick obtaining panoramic picture and depth information, and can be optimized by machine learning method and be calibrated
Parameter is to accumulate data, therefore, the quality of panoramic mosaic picture and the precision of panorama depth information is promoted, to simplify 3D
Depth algorithm simultaneously improves computational efficiency.Furthermore, it is possible to be implanted into simplified 3D depth algorithm, executed on single-chip microcontroller, therefore fish
The image calibration system of eye camera can be calibrated immediately, easy to carry.In addition, by the required production calibration process of simplification and saving
It saves time, and while panorama fisheye camera shoots target, object space is scanned using three-dimensional laser scanner,
Three-dimensional image is generated, compares calibration with above-mentioned 3D panoramic image, it is further provided the authenticity of image.
Detailed description of the invention
Fig. 1 is flow chart of the invention；
Fig. 2 is system diagram of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Herein
Described specific embodiment is only used to explain the present invention, is not intended to limit the present invention.Based on the embodiments of the present invention,
Every other embodiment obtained by those of ordinary skill in the art without making creative efforts, belongs to this hair
The range of bright protection.
The present invention provides the image calibration of panorama fish eye camera as shown in Figure 1, suture and depth reconstruction method, packet
Include following steps:
S100: finding object space, carries out creation panoramic optical object space；
S120: it is shot using panoramic picture of the panorama fish eye camera to the panoramic optical object space；
S130: the inner parameter calibrating patterns of creation panorama fish eye camera；
S140: the image mosaic parameter model of creation panoramic picture and the panoramic optical object space；
S150: the spatial depth transformation parameter model of panoramic picture and the panoramic optical object space is established；
S160: image mosaic parameter model is utilized, the depth conversion parameter model in space and the calibrating die of inner parameter are made
Type generates 3D panoramic picture comprising panorama depth information；
S170: being scanned object space using three-dimensional laser scanner, makes the 3-D image of scanning and the 3D of generation
Panoramic image is compared, and calibrates to 3D panoramic image.
Specific in the present embodiment: it includes Optimal Parameters that described image, which splices parameter model, acquires inner parameter calibrating die
Type, described image splice parameter model and spatial depth, the transformation parameter model from each panorama fish eye camera.
Specific in the present embodiment: the Optimal Parameters are for optimizing inner parameter calibrating patterns, described image splicing ginseng
Exponential model and spatial depth are by means of the transformation parameter model of machine learning, and wherein algorithm used in machine learning includes supporting
Vector machine.
Specific in the present embodiment: the Optimal Parameters are for updating inner parameter calibrating patterns, described image splicing ginseng
Exponential model and spatial depth conversion parameter model.
The present invention provides the image calibration of panorama fish eye camera as shown in Figure 2, suture and depth reconstruction system, packet
The panorama fish eye camera and three-dimensional laser scanner are included, the panorama fish eye camera includes four fish eye lenses, four
Cmos sensor module and panoramic picture and panorama depth information module, wherein the adjacent fish-eye shooting direction
The angle of cut is 90 degree；The panoramic picture and panorama depth information module include inner parameter calibration module and are stored therein interior
Portion's parametric calibration model, wherein the inner parameter calibration module is used to provide the coordinate transform mould between coordinate transformation model
The required parameter of type；The cmos sensor module includes image mosaic module and the described image being stored therein splicing parameter
Model, spatial depth transformation parameter module and the spatial depth transformation parameter model being stored therein, wherein described image splicing
The Panorama Mosaic that module is used to shoot the panorama fish eye camera is at panoramic pictures, the spatial depth transformation parameter
Module is used to provide the transformation model in 2D flat image and 3d space between Object Depth in the panorama fish eye camera,
Obtain panorama depth information；Each pixel and computing module in panoramic picture with it is deep for generating the panoramic picture and panorama
Spend information module electrical connection, wherein the pixel and computing module are used for calibration and spliced panoramic picture and panorama depth information,
To generate 3D panoramic picture.
In the present embodiment, specific: the computing module further includes optimization module, is electrically connected with the optimization module, is used
In generating panoramic picture and panorama depth information, wherein the optimization module can accumulate supplemental characteristic by from each described
Panorama fish eye camera collects inner parameter calibrating patterns, and described image splices parameter model and spatial depth transformation parameter mould
Then type passes through machine learning method Optimal Parameters data.
In the present embodiment, specific: algorithm used in the machine learning includes support vector machines.
It is specific: the inner parameter calibration module, described image splicing module and the spatial depth in the present embodiment
Transformation parameter module is integrated into one single chip or can be one single chip.
Working principle or structural principle: firstly, the image judgment object that cannot be directly shot from monocular vision camera
Depth, and due to the anamorphose of fish eye lens shooting, actual depth cannot be easily judged, therefore, in order to establish
Relationship between Object Depth in 3d space and 2D flat image, is first carried out step S100, and with panorama fisheye camera
Distance label several targets, be arranged in a space, finding out between the target in target and panoramic picture in space
Corresponding relationship before, due to fish-eye spherical form, fish eye lens shooting anamorphose therefore should find out flake
The corresponding relationship of fish eye lens and cmos sensor module in video camera, that is, find out internal calibration parameter, as a result, in the present invention
The middle step S130 that executes is shot to establish by single fish eye lens with establishing the inner parameter calibrating patterns of panorama fisheye camera
Image and practical panoramic picture between corresponding relationship to suture panoramic pictures, step S4 is executed, by utilizing target, such as chess
Four inspections of the black and white substitution of disk pattern, establish four fish-eye physics by detection clarification of objective point
Relationship between position and plane of delineation coordinate, after correcting four fish-eye relative positions, Ying Jianli image mosaic
Parameter model, the angle of the crossing of the adjacent fish-eye shooting direction in panorama fisheye camera are 90 degree, therefore presence is by adjacent
At least one Overlay scenes of the image of fish eye lens shooting, in step s 4, the image shot respectively from adjacent fish eye lens
In find out Overlay scenes, firstly, a pixel of the specified image shot by one of fish eye lens, and according to pixel around
Color change carrys out defined feature vector, then finds out corresponding pixel in the image of adjacent fish eye lens shooting, is establishing extremely
After the corresponding relationship of a few feature vector and pixel, that is, image mosaic parameter model is established, step S4 is completed, then executes step
Rapid S5 is utilizing panorama fisheye camera to establish the spatial depth transformation parameter model of panoramic picture and panoramic optical object space
After the panoramic picture of the panoramic optical object space of shooting, the panoramic picture and panorama of panoramic optical object space are obtained
The distance between the target position in optical target space and panorama fish, the depth of panoramic optical object space is to obtain panorama depth
Information, by executing step S1 to S5, the panoramic picture of panorama fisheye camera shooting, the inner parameter calibration of panorama fisheye camera
Model, image mosaic parameter model and the spatial depth transformation parameter model for obtaining panoramic picture and panoramic optical object space,
Then step S6 is executed to utilize image mosaic parameter model, and spatial depth transformation parameter model and inner parameter calibrating patterns come
The 3D panoramic picture including panorama depth information is generated, inner parameter calibration module is for storing above-mentioned inner parameter calibrating die
Type, and the coordinate transform between flake mirror and cmos sensor module is executed towards deformation pattern according to above-mentioned parameter model
The image mosaic that expires module passes through internal ginseng for storing above-mentioned image mosaic parameter model, i.e. external parameter calibrating patterns
Number calibration module splices panoramic picture adjusted to generate fish-eye shape, panoramic pictures, spatial depth transformation parameter
Module is for storing above-mentioned spatial depth transformation parameter model, 2D plane in the 3d space to find out the shooting of panorama fish eye camera
Corresponding relationship between image and actual object depth obtains the panorama depth information of each pixel in panoramic picture, finally adopts
Object space is scanned with three-dimensional laser scanner, generates three-dimensional image, is carried out pair with above-mentioned 3D panoramic image
Than calibration, it is further provided the authenticity of image.
Finally, it should be noted that the foregoing is only a preferred embodiment of the present invention, it is not intended to restrict the invention,
Although the present invention is described in detail referring to the foregoing embodiments, for those skilled in the art, still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features,
All within the spirits and principles of the present invention, any modification, equivalent replacement, improvement and so on should be included in of the invention
Within protection scope.
Claims (8)
1. the image calibration of panorama fish eye camera, suture and depth reconstruction method, characterized by the following steps:
S100: finding object space, carries out creation panoramic optical object space；
S120: it is shot using panoramic picture of the panorama fish eye camera to the panoramic optical object space；
S130: the inner parameter calibrating patterns of creation panorama fish eye camera；
S140: the image mosaic parameter model of creation panoramic picture and the panoramic optical object space；
S150: the spatial depth transformation parameter model of panoramic picture and the panoramic optical object space is established；
S160: utilizing image mosaic parameter model, and the calibrating patterns of the depth conversion parameter model and inner parameter that make space come
Generate 3D panoramic picture comprising panorama depth information；
S170: being scanned object space using three-dimensional laser scanner, makes the 3-D image of scanning and the 3D panorama of generation
Figure is compared, and calibrates to 3D panoramic image.
2. the image calibration of panorama fish eye camera according to claim 1, suture and depth reconstruction method, feature exist
In: it includes Optimal Parameters that described image, which splices parameter model, acquires inner parameter calibrating patterns, and described image splices parameter model
And spatial depth, the transformation parameter model from each panorama fish eye camera.
3. the image calibration of panorama fish eye camera according to claim 1, suture and depth reconstruction method, feature exist
In: Optimal Parameters for optimizing inner parameter calibrating patterns, described image splice parameter model and spatial depth by means of
The transformation parameter model of machine learning, wherein algorithm used in machine learning includes support vector machines.
4. the image calibration of panorama fish eye camera according to claim 1, suture and depth reconstruction method, feature exist
In: the Optimal Parameters are for updating inner parameter calibrating patterns, described image splicing parameter model and spatial depth conversion ginseng
Exponential model.
5. the image calibration of panorama fish eye camera, suture and depth reconstruction system, it is characterised in that: including the panorama flake
Video camera and three-dimensional laser scanner, the panorama fish eye camera include four fish eye lenses, four cmos sensor modules
With panoramic picture and panorama depth information module, wherein the angle of cut of the adjacent fish-eye shooting direction is 90 degree；It is described
Panoramic picture and panorama depth information module include inner parameter calibration module and the inner parameter calibrating patterns that are stored therein,
Wherein, the inner parameter calibration module is used to provide the required parameter of the coordinate transformation model between coordinate transformation model；Institute
Stating cmos sensor module includes that image mosaic module and the described image being stored therein splicing parameter model, spatial depth become
The spatial depth transformation parameter model for changing parameter module and being stored therein, wherein described image splicing module is used for will be described
The Panorama Mosaic of panorama fish eye camera shooting is used at panoramic pictures, the spatial depth transformation parameter module described
Transformation model in 2D flat image and 3d space between Object Depth is provided in panorama fish eye camera, obtains panorama depth letter
Breath；Each pixel and computing module in panoramic picture with for generating the panoramic picture and panorama depth information module is electrically connected
It connects, wherein the pixel and computing module are for calibration and spliced panoramic picture and panorama depth information, to generate 3D panorama sketch
Picture.
6. the image calibration of panorama fish eye camera according to claim 5, suture and depth reconstruction system, feature exist
In: the computing module further includes optimization module, is electrically connected with the optimization module, for generating panoramic picture and panorama depth
Information, wherein the optimization module can accumulate supplemental characteristic by collecting internal ginseng from each panorama fish eye camera
Number calibrating patterns, described image splice parameter model and spatial depth transformation parameter model, then excellent by machine learning method
Change supplemental characteristic.
7. the image calibration of panorama fish eye camera according to claim 6, suture and depth reconstruction system, feature exist
In: algorithm used in the machine learning includes support vector machines.
8. the image calibration of panorama fish eye camera according to claim 5, suture and depth reconstruction system, feature exist
In: the inner parameter calibration module, described image splicing module and the spatial depth transformation parameter module are integrated into individually
Chip can be one single chip.
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Application publication date: 20190906 |