CN113689533A - High-definition modeling cloud rendering method - Google Patents
High-definition modeling cloud rendering method Download PDFInfo
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- CN113689533A CN113689533A CN202110884354.7A CN202110884354A CN113689533A CN 113689533 A CN113689533 A CN 113689533A CN 202110884354 A CN202110884354 A CN 202110884354A CN 113689533 A CN113689533 A CN 113689533A
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- 238000009877 rendering Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title claims abstract description 15
- 239000002131 composite material Substances 0.000 description 6
- 239000003086 colorant Substances 0.000 description 2
- 238000013499 data model Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/005—General purpose rendering architectures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/04—Texture mapping
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/08—Volume rendering
Abstract
The invention relates to a high definition modeling cloud rendering method comprising rendering a first image based on point cloud data at least in part on a location, the first image corresponding to a first view frustum, the point cloud data comprising a primary level and one or more sub-levels organizing data, a first sub-level of the plurality of sub-levels organized using a plurality of minutiae points, a second sub-level of the plurality of sub-levels organized using a plurality of minutiae points, determining that a perspective has changed to a second view frustum, identifying that a first minutia of the first sub-level intersects the second view frustum, identifying a second minutia of the second sub-level intersecting the second view frustum, associating a point of the second minutia with a frame buffer object, and rendering a second image corresponding to the second view frustum based at least in part on the point associated with the frame buffer object for the first image at least in part on the location. The invention has the advantages that: and rendering the image by using the points of the highest-resolution frame buffer object to obtain a high-definition modeling rendering map.
Description
Technical Field
The invention relates to the technical field of modeling rendering, in particular to a high-definition modeling cloud rendering method.
Background
The cloud rendering mode is similar to that of conventional cloud computing, namely, the 3D program is placed in a remote server for rendering, the user terminal clicks a 'cloud rendering' button through Web software or directly in the local 3D program and accesses to the access resource through the high-speed internet, the instruction is sent out from the user terminal, the server executes a corresponding rendering task according to the instruction, and a rendering result picture is transmitted back to the user terminal for displaying.
At present, some three-dimensional modeling rendering methods of point cloud data exist, and the point cloud data can be visualized through the methods, but due to the fact that the amount of operation of the point cloud data is too large, the problems that the point cloud data cannot be completely displayed in a memory or the point cloud data can be rendered slowly can exist.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a high-efficiency high-definition modeling cloud rendering method.
In order to solve the technical problems, the technical scheme provided by the invention is as follows: a high definition modeling cloud rendering method comprising rendering a first image at least partially in place based on point cloud data, the first image having a first view frustum, the point cloud data comprising a primary level and one or more sub-levels organizing the data, a first sub-level of the plurality of sub-levels organized using a plurality of minutiae points, each minutiae point representing 1/8 of a root level, a second sub-level of the plurality of sub-levels organized using a plurality of minutiae points, each minutiae point representing 1/8 less than the root level, determining that a perspective has changed to the second view frustum, identifying that the first minutiae point of the first sub-level intersects the second view frustum, identifying a second minutiae point of the second sub-level intersecting the second view frustum, determining that a plurality of points are equal to one in a two-dimensional projection of the second minutiae point corresponding to each pixel on a plane represented by a frame buffer object, the point of the second minutiae point is associated with the frame buffer object and the first image is positioned to render a second image corresponding to the second view frustum based at least in part on the point associated with the frame buffer object.
Further, a point in a second minutia of the plurality of minutiae is projected into two dimensions, thereby generating a two-dimensional projection of the second minutia, a distance to the second minutia is determined, the number of points in the two-dimensional projection of the first minutia is determined to correspond to at least one per pixel on a plane represented by the frame buffer object based on the two-dimensional projection of the second minutia and the distance to the second minutia, and the second minutia associated with the frame buffer object is selected.
Further, a point in a first minutia of the plurality of minutiae is projected into two dimensions, thereby generating a two-dimensional projection of the first minutia, a distance to the first minutia is determined, the first minutia is determined based on the two-dimensional projection of the first minutia and the distance to the first minutia, a corresponding number of points per pixel in the two-dimensional projection of the first minutia on a plane represented by the frame buffer object is greater than one, and the first minutia is prohibited from being associated with the frame buffer.
Further, the points used in rendering the first image are re-projected into a plurality of different resolution frame buffer objects, including a frame buffer object of the first resolution and a second frame buffer object of a second resolution, wherein the second resolution is higher than the first resolution, the frame buffer objects are determined from receiving points from the second minutiae points, and whether at least one of the points received corresponds to the same location in the frame buffer object as the point re-projected into the frame buffer object.
After adopting the structure, the invention has the following advantages: determining, by a point cloud data model, for each voxel or cell, an average color of points falling within a space represented by the voxel, and may create a composite point at the center of the voxel with the average color, each point data in the original point cloud may be associated with a single voxel, the colors may be averaged using a brightness preserving technique, generating a composite point representing the average color of the points in each voxel, determining whether a highest resolution representation of the point cloud has been generated until each cell within the highest resolution composite point cloud represents a particular volume of the scene, rendering the image with the points of the highest resolution frame buffer object, resulting in a high definition modeled rendering.
Detailed Description
The present invention is described in further detail below.
A high definition modeling cloud rendering method comprising rendering a first image at least partially in place based on point cloud data, the first image having a first view frustum, the point cloud data comprising a primary level and one or more sub-levels organizing the data, a first sub-level of the plurality of sub-levels organized using a plurality of minutiae points, each minutiae point representing 1/8 of a root level, a second sub-level of the plurality of sub-levels organized using a plurality of minutiae points, each minutiae point representing 1/8 less than the root level, determining that a perspective has changed to the second view frustum, identifying that the first minutiae point of the first sub-level intersects the second view frustum, identifying a second minutiae point of the second sub-level intersecting the second view frustum, determining that a plurality of points are equal to one in a two-dimensional projection of the second minutiae point corresponding to each pixel on a plane represented by a frame buffer object, the point of the second minutiae point is associated with the frame buffer object and the first image is positioned to render a second image corresponding to the second view frustum based at least in part on the point associated with the frame buffer object.
Further, a point in a second minutia of the plurality of minutiae is projected into two dimensions, thereby generating a two-dimensional projection of the second minutia, a distance to the second minutia is determined, the number of points in the two-dimensional projection of the first minutia is determined to correspond to at least one per pixel on a plane represented by the frame buffer object based on the two-dimensional projection of the second minutia and the distance to the second minutia, and the second minutia associated with the frame buffer object is selected.
Further, a point in a first minutia of the plurality of minutiae is projected into two dimensions, thereby generating a two-dimensional projection of the first minutia, a distance to the first minutia is determined, the first minutia is determined based on the two-dimensional projection of the first minutia and the distance to the first minutia, a corresponding number of points per pixel in the two-dimensional projection of the first minutia on a plane represented by the frame buffer object is greater than one, and the first minutia is prohibited from being associated with the frame buffer.
Further, the points used in rendering the first image are re-projected into a plurality of different resolution frame buffer objects, including a frame buffer object of the first resolution and a second frame buffer object of a second resolution, wherein the second resolution is higher than the first resolution, the frame buffer objects are determined from receiving points from the second minutiae points, and whether at least one of the points received corresponds to the same location in the frame buffer object as the point re-projected into the frame buffer object.
In particular, the present invention determines, for each voxel or cell, an average color of points falling within the space represented by the voxel through a point cloud data model, and may create a composite point at the center of the voxel with the average color, each point data in the original point cloud may be associated with a single voxel, the colors may be averaged using a brightness preserving technique, a composite point representing the average color of points in each voxel is generated, it is determined whether a highest resolution representation of the point cloud has been generated until each cell within the highest resolution composite point cloud represents a particular volume of the scene, the image is rendered with the points of the highest resolution frame buffer object, resulting in a high definition modeled rendering.
The present invention and its embodiments have been described above, but the description is not limitative, and the actual structure is not limited thereto. It should be understood that those skilled in the art should understand that they can easily make various changes, substitutions and alterations herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (4)
1. A high-definition modeling cloud rendering method is characterized by comprising the following steps: including rendering a first image at least partially in place based on point cloud data, the first image corresponding to a first view volume, the point cloud data including a primary level and one or more sub-levels organizing the data, a first sub-level of the plurality of sub-levels organized using a plurality of minutiae points, each minutiae point representing 1/8 of a root level, a second sub-level of the plurality of sub-levels organized using a plurality of minutiae points, each minutiae point representing 1/8 less than the root level, determining that the perspective has become the second view volume, identifying that the first minutiae point of the first sub-level intersects the second view volume, identifying a second minutiae point of the second sub-level intersecting the second view volume, determining that a plurality of points equal to one in a two-dimensional projection of the second minutiae point corresponding to each pixel on a plane represented by the frame buffer object, associating the point of the second minutiae point with the frame buffer object, and the first image is positioned to render a second image corresponding to the second view frustum based at least in part on the point associated with the frame buffer object.
2. The high-definition modeling cloud rendering method according to claim 1, characterized in that: projecting points in a second minutia of the plurality of minutiae into two dimensions, thereby generating a two-dimensional projection of the second minutia, determining a distance to the second minutia, determining a number of points in the two-dimensional projection of the first minutia corresponding to at least one per pixel on a plane represented by the frame buffer object based on the two-dimensional projection of the second minutia and the distance to the second minutia, and selecting the second minutia associated with the frame buffer object.
3. The high-definition modeling cloud rendering method according to claim 1, characterized in that: projecting a point in a first minutia of the plurality of minutiae into two dimensions, thereby generating a two-dimensional projection of the first minutia, determining a distance to the first minutia, determining the first minutia based on the two-dimensional projection of the first minutia and the distance to the first minutia, the number of points in the two-dimensional projection of the first minutia corresponding to each pixel on a plane represented by the frame buffer object being greater than one, and prohibiting the first minutia from being associated with the frame buffer object.
4. The high-definition modeling cloud rendering method according to claim 1, characterized in that: re-projecting points used in rendering the first image into a plurality of different resolution frame buffer objects, including a frame buffer object of a first resolution and a second frame buffer object of a second resolution, wherein the second resolution is higher than the first resolution, determining the frame buffer object from points received from the second minutiae point, determining whether at least one of the points received corresponds to a same location in the frame buffer object as the point re-projected into the frame buffer object.
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| CN202110884354.7A CN113689533A (en) | 2021-08-03 | 2021-08-03 | High-definition modeling cloud rendering method |
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| US8281281B1 (en) * | 2006-06-07 | 2012-10-02 | Pixar | Setting level of detail transition points |
| CN107886561A (en) * | 2017-11-30 | 2018-04-06 | 公安部物证鉴定中心 | Storage scheduling and display methods based on scene of a crime cloud data |
| CN111179394A (en) * | 2019-11-25 | 2020-05-19 | 苏州智加科技有限公司 | Point cloud scene rendering method, device and equipment |
| CN112002019A (en) * | 2020-08-25 | 2020-11-27 | 成都威爱新经济技术研究院有限公司 | Method for simulating character shadow based on MR mixed reality |
| US20210209738A1 (en) * | 2017-06-02 | 2021-07-08 | Wisconsin Alumni Research Foundation | Systems, methods, and media for hierarchical progressive point cloud rendering |
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2021
- 2021-08-03 CN CN202110884354.7A patent/CN113689533A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8281281B1 (en) * | 2006-06-07 | 2012-10-02 | Pixar | Setting level of detail transition points |
| US20210209738A1 (en) * | 2017-06-02 | 2021-07-08 | Wisconsin Alumni Research Foundation | Systems, methods, and media for hierarchical progressive point cloud rendering |
| CN107886561A (en) * | 2017-11-30 | 2018-04-06 | 公安部物证鉴定中心 | Storage scheduling and display methods based on scene of a crime cloud data |
| CN111179394A (en) * | 2019-11-25 | 2020-05-19 | 苏州智加科技有限公司 | Point cloud scene rendering method, device and equipment |
| CN112002019A (en) * | 2020-08-25 | 2020-11-27 | 成都威爱新经济技术研究院有限公司 | Method for simulating character shadow based on MR mixed reality |
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