CN116939186B - Processing method and device for automatic associative covering parallax naked eye space calculation - Google Patents

Abstract

The embodiment of the invention provides a processing method and a device for automatic associatively covering parallax naked eye space calculation, wherein the method comprises the following steps: acquiring first characteristic data of a physical image sequence source of an input source; reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, and fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data; adjusting the coverage of the fusion data to determine the spatial parallax parameter change of the three-dimensional panoramic space; converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image; adjusting and converting the space parameters to obtain second characteristic data; combining the second characteristic data with the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data; and outputting the stereoscopic effect image in real time according to the combined data. The method can accurately control the parallax effect of naked eye parallax, so that an observer can see better stereoscopic effect.

Description

Processing method and device for automatic associative covering parallax naked eye space calculation

Technical Field

The invention relates to the technical field of 3D display algorithms, in particular to a processing method and a processing device for automatic associativity covering parallax naked eye space calculation.

Background

The existing 3D manufacturing has many modes, wherein the most common mode is to adopt a plurality of actual cameras to shoot real positions, then calculate stereoscopic viewing through viewing of a plurality of positions, and finally play in corresponding stereoscopic projection or playing equipment.

The 3D video on the market usually adopts a 2D screen, for example, a holographic film is pasted on a two-dimensional screen to realize a stereoscopic effect, but the method is complex to manufacture, expensive and poor in overall impression. The existing naked eye 3D is to realize the 3D effect of associative parallax through deception brain, size comparison among images and change of a reference object, but the effects are poor in image processing, and the method needs offline processing or manual calculation, has low efficiency, and can not directly obtain a two-dimensional image with a stereoscopic effect.

Disclosure of Invention

The embodiment of the invention aims to provide a processing method and a processing device for automatic associativity covering parallax naked eye space calculation, and the method can accurately control parallax effect of naked eye parallax, so that an observer can see better stereoscopic effect.

In order to achieve the above object, an embodiment of the present invention provides a processing method for automatic associative masking parallax naked eye space calculation, including:

acquiring first characteristic data of a physical image sequence source of an input source, wherein the input source is an image and/or a video;

reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, acquiring three-dimensional shooting data of the three-dimensional panoramic space, and fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data;

adjusting the coverage of the fusion data according to the parallax requirement of the required object so as to determine the spatial parallax parameter change of the three-dimensional panoramic space;

converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image;

the spatial parameters are adjusted and converted to obtain second characteristic data, wherein the second characteristic data are two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relation;

combining the second characteristic data with the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data;

And outputting the stereoscopic effect image in real time according to the combined data.

Optionally, the acquiring the first feature data of the physical image sequence source of the input source includes:

acquiring a plurality of images with different time and different directions in the input source, and mapping a two-dimensional image relationship into a three-dimensional space relationship;

extracting similar parallax relation image sequence data from the plurality of images to obtain first characteristic data;

the first characteristic data are parallax relation data of a physical image sequence source.

Optionally, the fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data includes:

the three-dimensional shooting data are space parallax relation parameters and shading parameters in a three-dimensional panoramic space;

the two-dimensional image is obtained by shooting the three-dimensional panoramic space with the adjusted coverage and parallax for the virtual camera; and acquiring the shading value and the parallax parameter of the three-dimensional shooting data, and fusing the three-dimensional shooting data and the two-dimensional image according to the shading value and the parallax parameter to obtain fused data.

Optionally, the adjusting the masking of the fusion data according to the parallax requirement of the requirement object to determine the spatial parallax parameter variation of the three-dimensional panoramic space includes:

Setting a shielding frame in the three-dimensional panoramic space to obtain a three-dimensional panoramic space with a required parallax relation;

shooting under the three-dimensional panoramic space by a virtual camera for changing the three-dimensional aspect ratio of the two-dimensional picture presented to the observer.

Optionally, the parallax obtaining method is at least one of an absolute parallax method, a graph cut method, a region matching method based on a fixed window and a left-right consistency method.

On the other hand, the invention also provides a processing device for automatically associatively covering parallax naked eye space calculation, which comprises:

the acquisition module is used for acquiring first characteristic data of a physical image sequence source of an input source, wherein the input source is an image and/or a video;

the first processing module is used for reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, obtaining three-dimensional shooting data of the three-dimensional panoramic space, and fusing the three-dimensional shooting data with the two-dimensional image to obtain fused data;

the second processing module is used for adjusting the coverage of the fusion data according to the parallax requirement of the required object so as to determine the spatial parallax parameter change of the three-dimensional panoramic space;

the third processing module is used for converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image;

The fourth processing module is used for adjusting and converting the space parameters to obtain second characteristic data, wherein the second characteristic data is two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relation;

a fifth processing module, configured to combine the second feature data and the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data;

and the output module is used for outputting the stereoscopic effect image in real time according to the combined data.

Optionally, the acquiring the first feature data of the physical image sequence source of the input source includes:

acquiring a plurality of images with different time and different directions in the input image source, and mapping a two-dimensional image relationship into a three-dimensional space relationship;

extracting similar parallax relation image sequence data from the plurality of images to obtain first characteristic data;

the first characteristic data are parallax relation data of a physical image sequence source.

Optionally, the fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data includes:

the three-dimensional shooting data are space parallax relation parameters and shading parameters in a three-dimensional panoramic space;

the two-dimensional image is obtained by shooting the three-dimensional panoramic space with the adjusted coverage and parallax for the virtual camera; and acquiring the shading value and the parallax parameter of the three-dimensional shooting data, and fusing the three-dimensional shooting data and the two-dimensional image according to the shading value and the parallax parameter to obtain fused data.

Optionally, the adjusting the masking of the fusion data according to the parallax requirement of the requirement object to determine the spatial parallax parameter variation of the three-dimensional panoramic space includes:

setting a shielding frame in the three-dimensional panoramic space to obtain a three-dimensional panoramic space with a required parallax relation;

shooting under the three-dimensional panoramic space by a virtual camera for changing the three-dimensional aspect ratio of the two-dimensional picture presented to the observer.

Optionally, the parallax obtaining method is at least one of an absolute parallax method, a graph cut method, a region matching method based on a fixed window and a left-right consistency method.

The processing method for automatic associativity covering parallax naked eye space calculation comprises the following steps: acquiring first characteristic data of a physical image sequence source of an input source, wherein the input source is an image and/or a video; reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, acquiring three-dimensional shooting data of the three-dimensional panoramic space, and fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data; adjusting the coverage of the fusion data according to the parallax requirement of the required object so as to determine the spatial parallax parameter change of the three-dimensional panoramic space; converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image; the spatial parameters are adjusted and converted to obtain second characteristic data, wherein the second characteristic data are two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relation; combining the second characteristic data with the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data; and outputting the stereoscopic effect image in real time according to the combined data. The invention is based on the technology developed by real-time manufacturing and artificial intelligence, effectively overcomes the disadvantages of the traditional naked eye 3D viewing technology, accelerates the manufacturing period, reduces the manufacturing cost, and enables an observer to see better stereoscopic effect by accurately controlling the parallax effect of naked eye parallax through the artificial intelligence.

Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.

Drawings

The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:

FIG. 1 is a schematic flow chart of a processing method for automatic associative masking parallax naked eye space calculation according to the present invention;

FIG. 2 is a schematic diagram of an embodiment of a processing method for automatic associative masking parallax naked eye spatial calculation according to the present invention;

FIG. 3 is a schematic representation of the projection of two-dimensional motion into three-dimensional space of the present invention;

FIG. 4 is a schematic diagram of the random variable relationship of the present invention;

FIG. 5 is a schematic representation of a three-dimensional panoramic image of the present invention;

FIG. 6 is a shading contrast diagram of the present invention;

FIG. 7 is a schematic view of a stereoscopic display space of the present invention;

fig. 8 is a schematic representation of another embodiment of the present invention.

Description of the reference numerals

501-a first planar masking;

502-second plane masking;

503-third plane masking;

504-fourth plane masking;

505-first effect diagram;

506-a second effect graph;

507-a first virtual camera;

601-a second virtual camera;

602-a third virtual camera;

701-a first stereoscopic display space;

702-a first three-dimensional panoramic space;

703-automatically filling a masking;

704-a first stereo disparity;

801-a first captured image;

802-a second captured image;

803-a data storage module;

804-a first data combination module;

805-a second three-dimensional panoramic space;

806-a second combining module.

Detailed Description

The following describes the detailed implementation of the embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.

Fig. 1 is a flow chart of a processing method of automatic associativity covering parallax naked eye space calculation according to the present invention, and as shown in fig. 1, the processing method of automatic associativity covering parallax naked eye space calculation according to the present invention includes:

step S101 is to acquire first feature data of a physical image sequence source of an input source, where the input source is an image and/or a video.

Specifically, the acquiring the first feature data of the physical image sequence source of the input source includes: acquiring a plurality of images with different time and different directions in the input source, and mapping a two-dimensional image relationship into a three-dimensional space relationship; extracting similar parallax relation image sequence data from the plurality of images to obtain first characteristic data; the first characteristic data are parallax relation data of a physical image sequence source.

According to a specific implementation mode, the method automatically identifies the physical image to obtain the data information of the image content, the identification image is identified based on the physical image sequence of the neural network, the physical image sequence provides rich information, the meaning of the physical image sequence is that the image information which cannot be obtained in the traditional image acquisition mode can be obtained by analyzing a plurality of frames of continuous images on the image processing image. Image data information is extracted in accordance with the time code by capturing pixel motion data of a physical image as data information of a physical image sequence source of an input source.

The first characteristic data is physical image sequence source data information obtained by AI module detection, AI module processing and some special program processing, and is a series of images sequentially and continuously obtained for targets at different times and different directions. The similarity of the pixel motion can be obtained by extracting the information component from each image sequence, namely the first characteristic data, wherein the first characteristic data is the image information for extracting the same parallax relation. And according to the first characteristic data, the analysis unit and the AI module intelligently realize signal conversion, and the converted signals are transmitted to the storage sequence unit to obtain second characteristic data. The second characteristic data refers to a data message which is obtained on the basis of the first characteristic data and is more reflected on the three-dimensional space. The analysis unit is mainly used for detecting pixel motion information and pixel targets, identifying pixels, tracking pixel targets and tracking motion targets from the first characteristic data, and estimating the three-dimensional motion of the motion pixels and the three-dimensional structural parameters thereof.

Step S102 is to reconstruct a three-dimensional panoramic space according to the two-dimensional image of the first feature data, obtain three-dimensional shooting data of the three-dimensional panoramic space, and fuse the three-dimensional shooting data with the two-dimensional image to obtain fused data.

Specifically, the fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data includes: the three-dimensional shooting data are space parallax relation parameters and shading parameters in a three-dimensional panoramic space; the two-dimensional image is obtained by shooting the three-dimensional panoramic space with the adjusted coverage and parallax for the virtual camera; and acquiring the shading value and the parallax parameter of the three-dimensional shooting data, and fusing the three-dimensional shooting data and the two-dimensional image according to the shading value and the parallax parameter to obtain fused data.

The stereoscopic display space in the invention belongs to a space concept, and dimension in physics is the number of space coordinates. Conventional naked eye 3D is typically a 3D effect that is seen by the human eye through screen parallax, using two screen displays or multiple screens to display. The virtual camera system obtains continuous images of the three-dimensional panoramic space according to requirements to display three-dimensional effects, and at least one three-dimensional panoramic space in the three-dimensional display space. When a plurality of three-dimensional panoramic spaces appear, a series of processes such as fusion and the like are carried out on the plurality of three-dimensional panoramic spaces, and the AI module is automatically adjusted. The number of the virtual cameras in the invention can be multiple, and the length, width and height of the space can be adjusted, so that the shooting parameters of the shooting system can be adjusted.

Step S103 is to adjust the masking of the fusion data according to the parallax requirement of the requirement object, so as to determine the spatial parallax parameter variation of the three-dimensional panoramic space.

Specifically, the adjusting the masking of the fusion data according to the parallax requirement of the requirement object to determine the spatial parallax parameter variation of the three-dimensional panoramic space includes: setting a shielding frame in the three-dimensional panoramic space to obtain a three-dimensional panoramic space with a required parallax relation; shooting under the three-dimensional panoramic space by a virtual camera for changing the aspect ratio of the two-dimensional picture presented to the observer. The parallax obtaining method is at least one of an absolute parallax method, a graph cut method, a region matching method based on a fixed window and a left-right consistency method.

According to a specific embodiment, according to the fusion data, the comprehensive module and the AI module automatically/manually analyze the parallax so as to adjust the plane coverage, so that the spatial parameters of the three-dimensional panoramic space are changed. The comprehensive module is used for calculating the complex system synthesis and comprises system integration and function realization. The integration of the system is to combine a plurality of components into a whole; the function implementation is to obtain three-dimensional information from different module groups according to the stereoscopic parallax degree according to the system requirement. The comprehensive module classifies, analyzes, calculates, integrates and adjusts the data of the three-dimensional panoramic space and the virtual cameras to obtain three-dimensional information. Each data parameter can be independently adjusted or can be automatically/manually modified. The comprehensive module integrates the information of the three-dimensional display space to calculate, when one data parameter is changed, other data parameters are changed, corresponding changes are automatically made, and the self-adaptive result is obtained in real time. The adjustment of the stereoscopic parallax is to calculate the parallax by adjusting the adjustable adjustment parameters of the plane mask.

Step S104 is to convert the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and obtain the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image.

According to a specific embodiment, according to the spatial parallax parameter change of the three-dimensional panoramic space, the imaging unit shoots the three-dimensional space with the spatial parallax parameter change, and performs depth rendering (primary channel rendering) on shadows, double-sided materials, reflection capturing and illumination shadows in the three-dimensional space to obtain three-dimensional space parameters such as peripheral color filling. The acquisition unit determines the working mode of the imaging unit according to the information input by the user so as to meet the requirement of the user. The acquisition unit consists of an information acquisition part and an information output part. The acquisition part has the task of obtaining three-dimensional data information from the imaging unit, including pixel spatial positions and pixel gray values. In the imaging unit, the pixel spatial position is provided by the user and the pixel gray value is output by the carrying unit device. The pixel space position refers to a coding value given by the imaging unit to each pixel point in the stereoscopic display space. The gray value refers to a gray value assigned to each pixel point in the stereoscopic display space by the imaging unit, which represents a difference in the position of each pixel point in the image in the pixel space. The acquisition unit obtains spatial parameter changes of the stereoscopic display space and the three-dimensional panoramic space, and the rendering module changes pixels of the changed part without changing pixels of the unchanged part.

Step S105 is to adjust and convert the spatial parameters to obtain second feature data, where the second feature data is two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relationship.

Step S106 is to combine the second feature data and the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data.

According to a specific implementation mode, the spatial parameters are processed by the first processing module to obtain second characteristic parameters, and the control terminal transmits the second characteristic parameters and the three-dimensional shooting data to the data combination module to obtain combined data. Parameters such as shooting data field angle (fov), sensor, focal length, deformation perspective and the like obtained by the combination module from the imaging unit, adjustable parameter length, angle, width and the like of the plane shielding by the first processing module carried by the imaging unit, and calculation results of all data parameters by the combination module. And generating an effect image by adjusting the three-dimensional panoramic space of the shielding, obtaining a correct three-dimensional parallax relation, and combining the three-dimensional panoramic space with the shielding and the parallax field to obtain a two-dimensional image with a three-dimensional effect.

Step S107 is to output a stereoscopic image in real time according to the combination data.

According to a specific embodiment, the three-dimensional combined data are generated into a two-dimensional image of which the observer sees the three-dimensional effect, and the control terminal transmits the combined data to the display unit and the recording unit. The recording unit records all data, and the display unit outputs the effect stereoscopic image to the terminal in real time. The recording unit of the present invention is a unit that stores data between an operand and a storage unit. The conversion of the character string into binary digits can be achieved by the recording unit. The recording unit can compress the data to increase the transmission speed. The recording unit is located in the center of the system and is the main storage device for data in the present invention. The display unit outputs a stereoscopic display space to the terminal; the transmission unit transmits the combined data to the display unit and the recording unit. The display mode in the invention is through a three-dimensional display space. Before the display unit lines are displayed in the stereoscopic display space, the data stored in the recording unit are required to be checked, all the stored data are subjected to checksum rendering again by using a multiplexing technology, the obtained effect stereoscopic image is output to the control terminal, the control terminal displays the final effect stereoscopic image on the display unit in the stereoscopic display space, the effect stereoscopic image is a two-dimensional image which can be seen by an observer to have a three-dimensional effect, and the effect image is a two-dimensional image.

Fig. 2 is a schematic diagram of an embodiment of a processing method for automatic associative occlusion naked eye spatial calculation according to the present invention. As shown in fig. 2, the present invention includes an imaging unit for creating a virtual camera in a space to photograph and image the space; the comprehensive module is used for processing the length, width, angle and the like of the plane shielding web; the rendering module is used for performing depth rendering on shadows, double-sided materials, reflection capturing and illumination shadows in the space; the combination module is used for combining the data obtained by each part; and the display unit is used for displaying the finally presented effect.

First, physical image sequence source data information of an input source is acquired to obtain feature data. The input source (the input source includes a green screen image or the like) is recognized by the recognition unit. The identification unit is used for automatically identifying the physical image to obtain the data information of the image content. The identification image is based on the physical image sequence identification of the neural network, and the image information which is not obtained by the traditional image acquisition mode is obtained by analyzing a plurality of frames of continuous images on the image processing image. Image data information is extracted in accordance with the time code, and physical image sequence source data information is obtained by capturing pixel motion data of a physical image as an input source. The first characteristic data is the source data information of the physical image sequence obtained by AI module detection, AI module processing and some special program processing. And a series of images which are sequentially and continuously acquired for the target at different times and different directions. The similarity of the pixel motion can be obtained by extracting the components of the information from each image sequence, namely, the first characteristic data is obtained;

And according to the first characteristic data, the analysis unit and the AI module intelligently realize signal conversion, and the converted signals are transmitted to the storage sequence unit to obtain second characteristic data. The analysis unit is mainly used for detecting pixel motion information and pixel targets, identifying pixels, tracking pixel targets and tracking motion targets from the first characteristic data, and estimating the three-dimensional motion of the motion pixels and the three-dimensional structural parameters thereof. The analysis unit is also used for processing the signals of each module and each unit in frequency response, harmonic distortion and signal to noise ratio, and finally transmitting the signals to each player in an ideal state, and converting the electric signals into digital signals to realize signal conversion, so that the analysis unit meets the signal requirements of a plurality of types of each module and each unit.

And estimating the motion of the first characteristic data row, wherein the motion mainly comprises the motion of a shooting system and the motion of a target object in a scene, and the three-dimensional motion forms two-dimensional motion by projection on a two-dimensional image plane. Motion estimation includes model selection, estimation criteria, and search strategies. In the continuous image analysis processing, motion information is widely used for motion compensation (system conversion), filtering (denoising), restoration (deblurring), and the like. The parsing unit may also convert the digital signals into analog signals for providing analog data information for facilitating the imaging unit to select an optimal effect image. The analysis unit also has a classification function, and specifically comprises the step of classifying the physical image sequence source to obtain sequence information. The storage sequence unit can acquire the sequence in various modes, and obtain better images in real time (the better images refer to images with stronger quality, definition, saturation and contrast). The physical image sequence source is stored in the storage unit. The address to which an operand corresponds is often referred to as a memory location, i.e., a memory sequence. An operand herein refers to a group of instructions, not a string. In one memory sequence there are and only two elements, a value (or address) in one memory sequence unit and a value (or address) in another memory sequence unit. A memory sequence is a collection of instructions, each of which has one or more memory sequences, and each element is referred to as a byte or a word (bit) in the present invention. Each byte is made up of a set of symbols, and therefore the bytes are also referred to as "symbols" in this disclosure. All sequence information is stored in a storage sequence unit.

The application projects two-dimensional motion onto a three-dimensional space, and the following is the motion estimation of an analysis unit comprising: model selection, motion represents pixel motion, and modeling of motion edges and occlusions, etc. The core of the motion representation is the parameterization of the models of the motion field, the choice of these models and their parameters being application and scene objects dependent. Considering that an object point moves in a three-dimensional space, the position (camera coordinate system) of a target pixel at a time t is set, and the three-dimensional motion trail is a four-dimensional space-time curve, and for three-dimensional displacement of the target object or the target pixel at any two times. The relationship between the image sequence and the motion, the three-dimensional scene is projected onto a two-dimensional plane. Conventional approaches use two-dimensional motion to represent three-dimensional space-time. As shown in FIG. 3, the application converts two dimensions into three dimensions and simulates the two dimensions to three dimensions, and simulates the motion change on the three dimensions space axis to obtain simulation data, and estimates the data according to the simulation data. The three-dimension is composed of innumerable two-dimensions, so the illustration of achieving two-dimensional conversion to three-dimensions as shown in fig. 3 below projects innumerable two-dimensional moving points into three-dimensional space.

The estimation criteria when estimating the simulation data, i.e. the optimization criteria of model parameters in motion estimation, are various in form, such as uniform variance with respect to blocks, bayesian criteria, markov models, etc. The mean square error represents the variation degree of the first characteristic data, namely the pixel variation degree, is used for measuring the discrete degree of the data set, and can measure the variation degree from each pixel value in each set of characteristic data to the mean value of the data set, and the difference between the data sets is checked to be statistically significant (the difference between each pixel value and other values). The mean square error method is very useful for analyzing and predicting various data, and pixel variation data can be obtained by analyzing the first characteristic data.

The bayesian criterion is an optimization of the global first feature data, and the bayesian method is a representative application method in a discrete space and in a continuous space, which is more dependent on a continuous distribution. The Bayesian network reasoning algorithm is a statistical reasoning method based on a multivariate statistical analysis technology, the probability relation among event pixels is expressed through a directional graph, each pixel consists of nodes connected through directional arrows, each pixel node represents a random variable, each variable is mutually independent, and the arrows represent reasons and result relations among the variables. The sense of the arrow is that a change in one variable can cause a change in another variable. As shown in fig. 4, the bayesian network is causal probability for pixel behavior analysis. And obtaining pixel behavior analysis data. The pixel change in space is referred to as a random variable, and can be from A to E or from A-B-D-E. The motion track of the pixels can be various, and the motion track from one pixel point to another pixel point can be various. Fig. 4 is a random event generated by the motion state and motion trajectory of a pixel as random variables. The Bayesian rule and framework are reasoning about the distribution of continuous pixels, and are used for not only independently analyzing each pixel, but also performing multi-element statistics on continuous pixel changes.

After the pixel variation data and the pixel behavior analysis data of the first feature data are acquired, searching for strategies of the pixel variation data and the pixel behavior analysis data. The invention aims to achieve efficient performance and operating efficiency. The search strategy reflects state space methods including exhaustive methods, relaxed iterative methods, conditional iterative, and highest confidence priority methods. According to these methods, second feature data is obtained, which refers to the data of the final movement pattern of the pixel projected into the three-dimensional space. By transmitting the characteristic data to the imaging unit.

And according to the characteristic data, the imaging unit establishes a real-time virtual panoramic shooting system in the three-dimensional display space to obtain three-dimensional shooting data. The imaging unit transmits the three-dimensional shooting data information to the carrying unit to obtain a two-dimensional image, and the two-dimensional image is fused to the carrying unit to obtain fused data. The invention relates to a three-dimensional display space, which belongs to a space concept and belongs to the four-dimensional world. Conventional naked eye 3D typically achieves a 3D effect that is seen by the human eye through parallax, using a two screen display or multiple screens to display. The virtual camera system obtains continuous images of the three-dimensional panoramic space according to requirements to display three-dimensional effects by means of the reconstructed three-dimensional panoramic space. And at least one three-dimensional panoramic space is set in the stereoscopic display space. And automatically adjusting and fusing a plurality of three-dimensional panoramic spaces through the AI module. And arranging a plurality of virtual cameras in the three-dimensional panoramic space.

As shown in fig. 5, the object in the three-dimensional panoramic space may be any object, or may be an object in which a green curtain image is converted into three dimensions. In fig. 5, a first planar mask 501, a second planar mask 502, a third planar mask 503, and a fourth planar mask 504 are provided. The first plane mask 501 is an upper plane mask of the parallax mask, and the height, length, width, horizontal inclination angle, vertical inclination angle, etc. of the upper plane mask are adjustable parameters of the plane mask. The second plane mask 502, the third plane mask 503 and the fourth plane mask 504 are plane masks in different directions. The first effect map 505 and the second effect map 506 are three-dimensional panoramic images generated in a stereoscopic display space, respectively. The first virtual camera 507 is disposed between the covering panels, and there may be a plurality of virtual cameras for photographing objects in the three-dimensional panoramic space.

And determining a plurality of two-dimensional images based on a plurality of virtual cameras, and obtaining parallax images of the three-dimensional panoramic space by performing a global matching algorithm on the two-dimensional images. The corresponding relation diagram can also be established through judging the image space relation between a virtual camera and a real camera. The adjustable parameters of the four plane masking are adjusted, shooting parameters of the virtual camera are set, and the scene of the virtual camera is set by determining the position, the orientation, the view angle and other parameters of the camera to construct a view.

Specifically, the step of setting the scene of the virtual camera includes determining the position of the camera, determining the position of the camera in the virtual scene, and adjusting the position as required. The position should be selected in consideration of the desired photographing effect and angle; the orientation of the camera is determined, which determines the scene seen by the observer. The orientation may be changed by adjusting the rotation angle of the camera, or indicated by the target object; the field angle is set and determines the range of views that the camera can see. Smaller field angles can make the picture look more enlarged, and larger field angles can take a wider scene. The angle of the field of view can also be adjusted as required to achieve the desired effect; adjusting the parameters of the camera includes adjusting some additional parameters as needed to improve the shooting effect. Such as adjusting the focal length, aperture, shutter speed, etc. of the camera to achieve the desired visual effect. Testing and adjusting includes that after the camera scene is set, testing can be performed and adjusting can be performed as needed. As a result, the position, orientation and parameters of the camera can be adjusted again if not satisfied until the desired effect is achieved.

By adjusting the position, orientation, field angle, and other parameters of the camera, a visually attractive scene may be created. And adjusting the adjustable parameters of the plane shielding and the shooting parameters of the virtual camera to obtain different three-dimensional panoramic images. The three-dimensional panoramic image in the application is a three-dimensional parallax relationship based on human visual reconstruction. Wherein objects in the three-dimensional panoramic space can be replaced at will.

The carrying unit is used for binding the virtual camera and the plane shielding plate, and the plane shielding plate moves along with the virtual camera when the virtual camera moves, and each parameter of the plane shielding plate and the virtual camera can be adjusted. The length, angle and width of the shielding frame can be adjusted, and two-dimensional images shot by the virtual camera in the imaging unit are images with different effects. And adjusting parameters of the plane coverage by the first processing module to obtain fusion data.

The difference between the object in the image and the boundary of the black selected area can be clearly seen through the first effect diagram 505 and the second effect diagram 506, and the black boundary, namely the first plane shielding plate 501, the second plane shielding plate 502, the third plane shielding plate 503 and the fourth plane shielding plate 504, changes the parallax relation in space by adjusting the shielding plates. The required object can adjust the covering according to the required parallax relation, and the adjusting covering imaging unit shoots the adjusted three-dimensional panoramic space machine to obtain combined effect images in real time, wherein the effect images are shown as a first effect graph 505 and a second effect graph 506 in fig. 5.

And according to the fusion data, the comprehensive module and the AI module automatically/manually analyze parallax, and adjust the plane coverage so as to change the spatial parameters of the three-dimensional panoramic space. First, the synthesis module performs computation (the synthesis module refers to computation on complex systems, and various links exist between the modules/units, so as to form a complex system). The adjustment of the stereoscopic parallax is to calculate the parallax by adjusting the adjustable adjustment parameters of the plane mask.

In the process of reconstructing the three-dimensional panoramic space, a parallax field is established in the three-dimensional space, so that pictures seen by an observer are different, and the observer sees stereoscopic images.

The parallax calculation mode comprises an absolute parallax method, a graph cutting method, a region matching method based on a fixed window and a left-right consistency constraint principle.

The absolute parallax method is to establish correct left-view and right-view parallaxes in a stereoscopic display space. Luminance values of absolute difference maps of left and right views. The absolute difference map is simple in calculation mode and high in speed.

The graph cut method is a global matching algorithm, and is a main algorithm of stereo matching. The matching condition of the stereo image is represented by a global energy function, and the global energy function is minimized, so that the parallax image of the stereo image, namely the framework of a global stereo matching algorithm, is obtained. The global stereo matching algorithm can avoid common errors in many regional stereo matching algorithms, and has good performance in low texture regions. Graph cut is a representative algorithm of the global matching algorithm. And optimizing the areas with the parallax equal to a certain value in all the parallax maps at one time. The algorithm adopts the thought of a graph cut method, and redistributes and adjusts the relation between the original pixels and the parallax values according to the correlation degree of the adjacent points and the matching degree of the adjacent points and the assumed parallax, and converts the three-dimensional matching problem into the problem of solving the maximum flow minimum cut until the global energy function is minimized.

The region matching method based on the fixed window comprises the following steps: the simplest form of region matching is to divide the whole image into a number of sub-regions and then perform a similarity measure on the luminance information or gray distribution information of all the sub-regions. A window is created by taking a point to be matched of a reference diagram as a center, and when the window size is fixed, the region matching method is based on the fixed window. The pixel is characterized by the gray value distribution in the window, then such a pixel is searched in the alignment chart, the same window is created by taking the pixel as the center, the gray value distribution of the neighborhood pixel is characterized by the gray value distribution of the neighborhood pixel, the optimal matching is searched according to the constraint of the matching criterion, and the similarity between the two pixels must meet a certain threshold value condition. The essence is to use the correlation of gray information between local windows to quantize the image pair into a number of image blocks to determine the corresponding region.

The left-right consistency constraint principle comprises: one pixel point can only correspond to one disparity value, and this constraint is called a unique constraint in stereo matching. Since there are no more than two disparity values in a pixel, this constraint can also be described as a one-to-one correspondence between the matching points in the reference image and the target image, i.e., a left-right consistency constraint. After the left-right consistency detection, an inaccurate part is eliminated, the accuracy of the acquired depth information is improved, and the speed of calculating the regional disparity map subjected to the left-right consistency detection is also high.

The disparity map calculated by the graph cut method is most accurate, but its speed is very slow. According to the application, the AI module adopts different parallax processing methods according to different views, and when the graph cut method is used, the AI module assists in calculation so as to obtain a calculation result in real time. In the application, several modes for processing parallax are used for determining an absolute parallax method, a graph cut method, a region matching method based on a fixed window and a left-right consistency constraint principle. The method combines several modes for use, and the absolute parallax is calculated in a simple and fast way; the graph cut method uses a global matching algorithm to realize the establishment of parallax, and the graph cut method calculates the most accurate parallax; the disparity map calculated using the fixed window-based region matching method is very poor in accuracy, but it is very fast. After the left-right consistency detection, an inaccurate part is eliminated, the accuracy of the acquired depth information is improved, and the speed of calculating the regional disparity map subjected to the left-right consistency detection is also high.

The masking process has the effect of changing the proportion of the picture, and after the masking is added to the film by the composition, the aspect ratio of the picture can be changed, so that the method is more in line with the aesthetic feeling of human eyes. For example, the mask change is a change in which the ratio of the frames is changed to 16:9 by adding the mask, and the left image in fig. 6 refers to a plane mask, and an image with a changed light shade is obtained by the second virtual camera 601. As shown in the right diagram of fig. 6, the irregular coverage of the space does not affect the original illumination in the three-dimensional panoramic space when the third virtual camera 602 acquires the photographed image. The traditional processing method is to process the images frame by frame, draw the mask of the characters and the objects according to a certain mode and then process the single frame or process the continuous frames. The application establishes the space coverage in space, so that the virtual camera shoots under the space coverage, continuously and real-timely obtains the three-dimensional panoramic image with the right parallax established, calculates and produces the shooting image in real time.

The AI module automatically adjusts the picture proportion according to the panoramas displayed. The composition is perceived as better looking when viewed by an observer. Some parts need to be masked when a 3D effect is required to achieve a macroscopic 3D effect and not to affect the viewing effect. As shown in fig. 7, fig. 7 includes a first stereoscopic display space 701, a first three-dimensional panoramic space 702, an auto-fill mask 703, and a first stereoscopic parallax 704. The coverage represents that after the three-dimensional panoramic space is reconstructed, the three-dimensional panoramic space is displayed in a 3D mode, and the AI module automatically fills the outer area of the three-dimensional panoramic space, so that an observer can see better stereoscopic effect.

Among them, stereoscopic parallax is also called stereoscopic vision, stereoscopic perception. Depth perception based on binocular parallax. The effect of stereoscopic techniques is produced by creating parallax in the image. The parallax adjustment of the three-dimensional panoramic space is mainly used for convergence adjustment and parallax correction, and a quick estimation method of the stereoscopic parallax adjustment is established for accurately calculating the value range of the parallax adjustment quantity of the stereoscopic image. The AI algorithm first applies simulated human vision fusion to a three-dimensional panoramic space for display in a stereoscopic display space. And deducing the adjustment quantity of the parallax of the fusion area of the stereoscopic display screen. And finally, rapidly estimating a fusion area through sparse matching of depth cues of the three-dimensional panoramic space. The range of parallax adjustment is accurately obtained, the three-dimensional panorama space is displayed on the screen to the maximum extent, and the observer can see different 3D effects from a plurality of angles. Fig. 7 realizes the fusion of two spaces, and the interaction and fusion of the three-dimensional display space and the three-dimensional panoramic space are performed, and the AI module adjusts the stereo parallax and the coverage of the three-dimensional display space and the positioning and tracking of the AI module and the virtual camera.

The stereoscopic display space is used for displaying the 3D image and at least one three-dimensional panoramic space, and the stereoscopic parallax simulation unit is used for simulating the display state in the stereoscopic display space. In the invention, the stereo parallax simulation unit is used for simulating the difference between directions of at least two positions of an observer for seeing the same object. Parallax can be expressed in terms of the opening angle at the object of the distance (also called the baseline) between a number of different positions of the observer, with a simple triangular relationship between the parallax of the object and the distance of the object from the observer. The distance of the object can be determined by measuring the parallax of the object. The AI module automatically adjusts data parameters in space, space mask, space length, space angle, space object material, space depth, space illumination effects, space color fill, space depth rendering (all depth maps of one space, depth map rendering), space shading, and space color fusion thereof, space color fill, and space length, width, height, etc. when multiple three-dimensional panoramic spaces exist.

Each data parameter can be automatically adjusted by the AI module in the comprehensive module, and also can be manually adjusted. The comprehensive module can efficiently calculate all data required by the system, and obtain result data in real time. The comprehensive module and the AI module analyze and calculate all the second characteristic data to obtain result data, and the imaging unit rebuilds a three-dimensional panoramic space according to the information of the result data; the imaging unit reconstructs a three-dimensional panoramic space. The imaging unit rebuilds the three-dimensional panoramic space and the three-dimensional display space, the imaging unit transmits the analog data information to the output unit after the analog signals are processed by amplifying, shrinking, rotating, filtering, isolating and the like, the output unit is combined with the imaging unit, and the three-dimensional panoramic space, the correct shielding relation and the correct parallax relation are displayed in the three-dimensional display space. The imaging unit ensures definition and stereoscopic impression of the image. The three-dimensional panoramic space in the present invention is three-dimensionally displayed in real time, not two-dimensionally displayed. The method is equivalent to the fact that a three-dimensional panoramic space exists in the three-dimensional display space, and at least one virtual camera is built in the three-dimensional display space and can track the three-dimensional panoramic space in real time to obtain a three-dimensional panoramic image in the three-dimensional panoramic space. And transmitting the three-dimensional information in the stereoscopic display space to the carrying unit. The three-dimensional information in the stereoscopic display space comprises three-dimensional panoramic space information, data information of a virtual camera, space shading information, stereoscopic parallax distance information and other three-dimensional data information.

According to the space parallax parameter change of the three-dimensional panoramic space, the imaging unit shoots the three-dimensional space with the space parallax parameter change, and obtains three-dimensional space parameters such as shadows, double-sided materials, reflection capturing, depth rendering of illumination shadows, main channel rendering and peripheral color filling in the three-dimensional space. The function of the acquisition unit is to determine the working mode of the imaging unit according to the information input by the user so as to meet the user requirement. The acquisition unit consists of an information acquisition part and an information output part. Wherein the information acquisition unit of the acquisition part acquires three-dimensional data information from the imaging unit. The spatial position of the pixels in the imaging unit is provided by the user and the pixel gray values are output by the carrying unit device. The pixel space position refers to a coding value given by the imaging unit to each pixel point in the stereoscopic display space. The gray value refers to a gray value assigned to each pixel point in the stereoscopic display space by the imaging unit, which represents a difference in the position of each pixel point in the image in the pixel space.

And according to the space parameters, obtaining first processing data through a first processing module, and transmitting the first processing data and the three-dimensional shooting data to a data combination module by the control terminal to obtain combined data. As shown in fig. 8, the first shot image 801 is a shot image of a virtual camera, and the second shot image 802 is a shot image of another virtual camera when there are a plurality of virtual cameras, and further includes a data storage module 803, a first data combination module 804, a second three-dimensional panoramic space 805, and a second combination module 806. The output unit firstly transmits the multi-space fusion data to the first processing module. The output unit is AI automatic transmission, orderly and stable transmission data, and error information is automatically screened out at the output unit, so that the transmission data cannot be wrong and system disorder cannot be caused. Each pixel value information in the multispatial fusion data is calculated in real time in the first processing module. The first processing module is a spatial masking, which requires a value calculation for each pixel in each space to be converted into a binary digital signal. After the calculation of the value AI and the comprehensive calculation of each pixel point are completed, binary encoding can be performed. Four dimensions are made up of innumerable three-dimensional spaces, and three dimensions are made up of innumerable two-dimensional images. In the prior art it is difficult to directly convert a grey scale image into a binary signal, as this process introduces considerable distortion. However, the invention solves the problem of image distortion, and each pixel of the space is subjected to lossless change in the three-dimensional space, so that a high-definition three-dimensional panoramic space is obtained. For example, only a portion of the pixels in a gray image space can be seen, and a considerable error is introduced because each pixel in the gray image space needs to perform a value calculation (generally called a gray value). The first processing module, the synthesis module, the analysis unit and the AI module cooperate to calculate the pixel. The analysis unit calculates the changed pixels and the unchanged pixels are not calculated, so that the analysis unit obtains the pixel information and classifies the pixels to obtain the data information of the changed pixels and the unchanged pixels. The comprehensive module calculates the changed pixels in real time, the comprehensive module obtains a calculation result in real time, the first processing module carries out encoding in real time to directly convert the gray level image into a binary digital signal, and the traditional processing can cause digital signal processing distortion; in the invention, special processing and AI screening error are carried out by the first processing module, so as to obtain the characteristic digital signal, the characteristic digital signal is not distorted, and the obtained result is lossless result data. And the multi-space fusion data is subjected to auxiliary processing by the first processing module and other modules to obtain lossless result data. And the output unit transmits the lossless result data to the rendering module, and renders the finally displayed effect stereoscopic image.

In the invention, the rendering module refers to the process of carrying out set transformation and space structure on the space, and the rendering module carries out mathematical transformation on the input space geometric figure, and the AI module assists in automatically adjusting the structure of the space and the space geometric transformation and converts the space geometric figure into a binary digital signal which can be identified by a computer. Since the pixels are formed by dots or lines, the pixels are converted into binary digital signals, and corresponding processing is needed to be performed on the pixels of each input space, and the AI module automatically generates corresponding processing results. The rendering processing unit mainly renders the gray image to generate a color image. The color space refers to a high-definition spatial pixel with high color fusion degree in the whole space. The color space is stored in the recording unit.

The rendering module obtains a high-definition stereoscopic display space and a three-dimensional panoramic space, and the output unit transmits the high-definition stereoscopic display space and the three-dimensional panoramic space to the combination module. The combination module refers to filtering, channel selection, quantization, filter bank, digital signal processing, power calculation, digital filter involvement, waveform synthesis and display in the combination module, and the combination module combines the coverage, parallax distance and stereoscopic parallax degree between spaces.

The application aims to solve the problems of loss and error codes of color pixels in the transmission process, the traditional mode can not display each pixel in an original image, but each three-dimensional panoramic space and a stereoscopic display space (the stereoscopic display space is more like a four-dimensional space concept, the stereoscopic display space is the space combining the three-dimensional panoramic space with a plurality of masks and parallax fields, and the spatial parameter in the stereoscopic display space is the spatial parameter in the application), and the phenomenon of losing data and transmitting error codes can not exist in a combination module, which cannot be realized by the traditional processing mode. The combination unit in the application can also automatically select the adaptive channel. The combining module can also perform power calculation, the combining module calculates the minimum power, and the AI module automatically matches the data distribution route and the data processing route so that the system consumes the minimum power. The conventional naked eye 3D has the problems of unclear images and unstable generated images caused by large power consumption, and the multiplexing technology is adopted in the application, namely, the data is processed again at the receiving end, and the AI modules are automatically matched. The multiplexing technology divides a stereoscopic display space into a plurality of independent three-dimensional panoramic spaces, then processes each subspace respectively, and finally combines the subspaces to output a complete stereoscopic display space, namely multiplexing. The application generates a plurality of high-definition three-dimensional panoramic spaces with the lowest power, and the pixel data of the three-dimensional display space is transmitted and sent in any state without loss and distortion and error codes.

And generating a two-dimensional image with three-dimensional effect seen by an observer from the three-dimensional combined data, transmitting the combined data to a display unit and a recording unit by a control terminal, recording all the data by the recording unit, and outputting the effect stereoscopic image to the terminal in real time by the display unit. A recording unit is a unit that stores data between an operand and a storage unit. The conversion of the character string into binary digits can be achieved by the recording unit. The recording unit can compress the data to increase the transmission speed. The recording unit is the main storage means of data in the present invention. The display unit outputs a stereoscopic display space to the terminal; the transmission unit transmits the combined data to the display unit and the recording unit. The display mode passes through the three-dimensional display space. Before the stereoscopic display space of the display unit line, the data stored in the recording unit is required to be checked, all the stored data are checked and rendered again by adopting a multiplexing technology, the obtained effect stereoscopic image is output to the control terminal, and the control terminal displays the final effect stereoscopic image on the display unit in the stereoscopic display space. The resulting effect image refers to a two-dimensional image with a three-dimensional effect presented to the observer, and the effect image itself refers to a two-dimensional image.

The processing method for automatic associativity covering parallax naked eye space calculation comprises the following steps: acquiring first characteristic data of a physical image sequence source of an input source, wherein the input source is an image and/or a video; reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, acquiring three-dimensional shooting data of the three-dimensional panoramic space, and fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data; adjusting the coverage of the fusion data according to the parallax requirement of the required object so as to determine the spatial parallax parameter change of the three-dimensional panoramic space; converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image; the spatial parameters are adjusted and converted to obtain second characteristic data, wherein the second characteristic data are two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relation; combining the second characteristic data with the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data; and outputting the stereoscopic effect image in real time according to the combined data. The invention is based on the technology developed by real-time manufacturing and artificial intelligence, effectively overcomes the disadvantages of the traditional naked eye 3D viewing technology, accelerates the manufacturing period, reduces the manufacturing cost, and enables an observer to see better stereoscopic effect by accurately controlling the parallax effect of naked eye parallax through the artificial intelligence.

The foregoing details of the optional implementation of the embodiment of the present application have been described in detail with reference to the accompanying drawings, but the embodiment of the present application is not limited to the specific details of the foregoing implementation, and various simple modifications may be made to the technical solution of the embodiment of the present application within the scope of the technical concept of the embodiment of the present application, and these simple modifications all fall within the protection scope of the embodiment of the present application.

In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, various possible combinations of embodiments of the present application are not described in detail.

Those skilled in the art will appreciate that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, including instructions for causing a single-chip microcomputer, chip or processor (processor) to perform all or part of the steps of the methods of the embodiments described herein. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

In addition, any combination of various embodiments of the present invention may be performed, so long as the concept of the embodiments of the present invention is not violated, and the disclosure of the embodiments of the present invention should also be considered.

Claims (8)

1. The processing method for automatic associative masking parallax naked eye space calculation is characterized by comprising the following steps:

acquiring first characteristic data of a physical image sequence source of an input source, wherein the input source is an image and/or a video;

reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, acquiring three-dimensional shooting data of the three-dimensional panoramic space, and fusing the three-dimensional shooting data and the two-dimensional image to obtain fused data;

adjusting the coverage of the fusion data according to the parallax requirement of the required object so as to determine the spatial parallax parameter change of the three-dimensional panoramic space;

converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image;

the spatial parameters are adjusted and converted to obtain second characteristic data, wherein the second characteristic data are two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relation;

Combining the second characteristic data with the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data;

outputting a stereoscopic effect image in real time according to the combined data;

the first characteristic data are parallax relation data of a physical image sequence source;

the fusing of the three-dimensional shooting data and the two-dimensional image to obtain fused data comprises the following steps: acquiring a shading value and a parallax parameter of the three-dimensional shooting data, and fusing the three-dimensional shooting data and a two-dimensional image according to the shading value and the parallax parameter to obtain fused data;

the adjusting the coverage of the fusion data according to the parallax requirement of the required object to determine the spatial parallax parameter change of the three-dimensional panoramic space comprises the following steps:

setting a shielding frame in the three-dimensional panoramic space to obtain a three-dimensional panoramic space with a required parallax relation;

shooting under the three-dimensional panoramic space by a virtual camera for changing the three-dimensional aspect ratio of the two-dimensional picture presented to the observer.

2. The method of claim 1, wherein the acquiring the first characteristic data of the physical image sequence source of the input source comprises:

acquiring a plurality of images with different time and different directions in the input source, and mapping a two-dimensional image relationship into a three-dimensional space relationship;

And extracting similar parallax relation image sequence data from the plurality of images to obtain first characteristic data.

3. The method of claim 1, wherein the step of determining the position of the substrate comprises,

the three-dimensional shooting data are space parallax relation parameters and shading parameters in a three-dimensional panoramic space;

the two-dimensional image is obtained by shooting the three-dimensional panoramic space with the mask and the parallax adjusted by the virtual camera.

4. The method of claim 1, wherein the step of determining the position of the substrate comprises,

the parallax obtaining method is at least one of an absolute parallax method, a graph cut method, a region matching method based on a fixed window and a left-right consistency method.

5. A processing device for automatic associative masking parallax naked eye spatial calculation, the device comprising:

the acquisition module is used for acquiring first characteristic data of a physical image sequence source of an input source, wherein the input source is an image and/or a video;

the first processing module is used for reconstructing a three-dimensional panoramic space according to the two-dimensional image of the first characteristic data, obtaining three-dimensional shooting data of the three-dimensional panoramic space, and fusing the three-dimensional shooting data with the two-dimensional image to obtain fused data;

the second processing module is used for adjusting the coverage of the fusion data according to the parallax requirement of the required object so as to determine the spatial parallax parameter change of the three-dimensional panoramic space;

The third processing module is used for converting the three-dimensional panoramic space into a two-dimensional panoramic image according to the spatial parallax parameter change of the three-dimensional panoramic space, and acquiring the spatial parameter of the three-dimensional parallax relation of the two-dimensional panoramic image;

the fourth processing module is used for adjusting and converting the space parameters to obtain second characteristic data, wherein the second characteristic data is two-dimensional image pixel information from a three-dimensional space to a two-dimensional space with a correct parallax relation;

a fifth processing module, configured to combine the second feature data and the three-dimensional shooting data in the three-dimensional panoramic space to obtain combined data;

the output module is used for outputting the stereoscopic effect image in real time according to the combined data;

the first characteristic data are parallax relation data of a physical image sequence source;

the fusing of the three-dimensional shooting data and the two-dimensional image to obtain fused data comprises the following steps: acquiring a shading value and a parallax parameter of the three-dimensional shooting data, and fusing the three-dimensional shooting data and a two-dimensional image according to the shading value and the parallax parameter to obtain fused data;

the adjusting the coverage of the fusion data according to the parallax requirement of the required object to determine the spatial parallax parameter change of the three-dimensional panoramic space comprises the following steps:

Setting a shielding frame in the three-dimensional panoramic space to obtain a three-dimensional panoramic space with a required parallax relation;

shooting under the three-dimensional panoramic space by a virtual camera for changing the three-dimensional aspect ratio of the two-dimensional picture presented to the observer.

6. The apparatus of claim 5, wherein the acquiring the first characteristic data of the physical image sequence source of the input source comprises:

acquiring a plurality of images with different time and different directions in the input source, and mapping a two-dimensional image relationship into a three-dimensional space relationship;

and extracting similar parallax relation image sequence data from the plurality of images to obtain first characteristic data.

7. The apparatus of claim 5, wherein the three-dimensional photographing data is a spatial parallax relationship parameter and a shading parameter in a three-dimensional panoramic space;

the two-dimensional image is obtained by shooting the three-dimensional panoramic space with the mask and the parallax adjusted by the virtual camera.

8. The apparatus of claim 5, wherein the device comprises a plurality of sensors,

the parallax obtaining method is at least one of an absolute parallax method, a graph cut method, a region matching method based on a fixed window and a left-right consistency method.