CN111625093B - Dynamic scheduling display method of massive digital point cloud data in MR (magnetic resonance) glasses - Google Patents
Dynamic scheduling display method of massive digital point cloud data in MR (magnetic resonance) glasses Download PDFInfo
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Abstract
The invention discloses a dynamic scheduling display method of massive digital point cloud data in MR glasses, which comprises a point cloud and a lens, and is characterized by comprising the steps of firstly, importing current view angle frame data into incremental octree data, traversing the incremental octree data, and calculating the central point P of the point cloud projected on a screen through the coordinates of a certain level node Bn Bn Coordinates and pass through P Bn Calculating boundary point P En Coordinates; step two, dynamically scheduling by dynamically cutting the octree algorithm, and calculating and loading the P of the current view child node Bn in each frame Bn P En Unloading child nodes which are not in the current field of view, and obtaining a loading list An and An unloading list Rn; step three, traversing the element Ai in the loading list An, judging whether the element Ai is loaded or not, and rendering data; step four, traversing the elements Ri in the unloading list Rn, and judging whether the current Ri is loaded or not; step five, continuously traversing the next level of child nodes, and automatically supplementing the child nodes into Rn; sixth, return to the first step.
Description
Technical Field
The invention relates to the field of dynamic scheduling display in MR (magnetic resonance) glasses, in particular to a dynamic scheduling display method for massive digital point cloud data in MR glasses.
Background
Mixed reality technology (MR) is a further development of virtual reality technology that enhances the realism of the user experience by presenting virtual scene information in a real scene, and by placing an interactive feedback information loop between the real world, the virtual world and the user. Mixed reality is a set of technical combinations that not only provide new viewing methods but also new input methods, and all methods are combined with each other, thereby promoting innovation.
Mixed Reality (MR), which includes both augmented reality and augmented virtual, refers to a new visual environment created by merging the real and virtual worlds. Physical and digital objects coexist in the new visualization environment and interact in real time. Systems typically have three features: 1. virtual and real 2. In virtual three-dimensional (3D registration) 3. Real-time operation; the implementation of Mixed Reality (MR) is required in an environment that can interact with real world things. The key point of MR is to interact with the real world and acquire information in time.
The existing MR glasses cannot load all point cloud data into the memory for rendering at one time because the CPU/GPU calculation power and the memory space of the existing MR glasses are very limited, namely, the dynamic scheduling display of massive digital point cloud data in the MR glasses cannot be realized.
Disclosure of Invention
The technical problem solved by the invention is to provide a dynamic scheduling display method of massive digital point cloud data in MR glasses, which can adopt a dynamic scheduling method under the CPU/GPU computing power and memory space of the MR glasses, namely, each frame calculates and loads child node data visible in the current field of view, and unloads child nodes which are not in the current field of view; therefore, CPU/GPU computing power and memory space of the MR glasses are fully utilized, and dynamic scheduling display of point cloud data is realized.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the invention discloses a dynamic scheduling display method of massive digital point cloud data in MR glasses, which is characterized by comprising the following steps:
the first step: importing the current view frame data into incremental octree data, traversing the incremental octree data, and calculating the central point P projected on the screen by the coordinates of a certain level node Bn of the point cloud Bn Coordinates and pass through P Bn Calculating coordinates to obtain boundary point P En Coordinates;
and a second step of: calculating and loading the central point P of the current view child node Bn in each frame through dynamic scheduling of a dynamic cut octree algorithm Bn Boundary point P En Unloading child nodes which are not in the current field of view, and obtaining a loading list An and An unloading list Rn;
and a third step of: after the loading list An is obtained, traversing the elements Ai in the loading list An, judging whether the elements Ai are loaded or not, and rendering corresponding point cloud data;
fourth step: after obtaining an unloading list Rn, traversing elements Ri in the unloading list Rn, judging whether the current Ri is loaded or not, and unloading data in the Ri;
fifth step: continuing traversing the next level of child nodes and automatically supplementing the child nodes into Rn;
sixth step: returning to the first step, the rendering of the next frame is continued.
Preferably, in the first step, among the plurality of nodes Bn, a center point P projected on the screen is calculated according to coordinates of a certain level of nodes Bn Bn The coordinate P ', the transformation formula of each point P to the screen coordinate P' is:
wherein: p is the coordinates of Bn; the posture matrix data M0 of the position of the person is obtained in real time through an inertial navigation positioning system; obtaining an internal reference matrix Mi and a perspective projection matrix Mp of the micro projector by using a calibration flow provided by the MR glasses; and calculating according to the current MR glasses display resolution to obtain a window transformation matrix Mw.
Preferably, in the first step, the step is performed by P Bn Calculating coordinates to obtain boundary point P En The coordinates and the calculation formula are as follows:
P En ＝P Bn +V 0 *R n
wherein: by means of a posture matrix M of the position of the person 0 Calculating to obtain the head top direction V of the person wearing the MR glasses 0 Then taking the radius R of the outside surrounding sphere of Bn n Calculating boundary point P En 。
Preferably, in the second step, the dynamic scheduling method by dynamically cutting the octree algorithm includes: firstly, judging the display size of a certain level of node Bn projected to a lens; then the central point P of a certain level node Bn is obtained Bn One boundary point P En And converts them into screen coordinate data; if P Bn And P En The coordinates are all outside the screen range, or P Bn And P En The distance value of the coordinates is smaller than a specified threshold L, and the current node and all child nodes are removed from the rendering queue; otherwise, displaying the point cloud content of the current node, continuously traversing the next level of child nodes, judging whether the current node can be displayed, putting the current node into a loading list An which can be displayed, and putting the current node into An unloading list Rn which cannot be displayed; the element in An is Ai and the element in Rn is Ri.
Preferably, after the third step, the element Ai in the loading list An is traversed after the loading list An is obtained, and if the current Ai is already loaded, the current element Ai is skipped; if the current Ai is not loaded, loading the data request in the Ai, and rendering corresponding point cloud data.
Preferably, after the unloading list Rn is obtained in the fourth step and the fifth step, traversing the elements Ri in the unloading list Rn, if the current Ri is not loaded, skipping the current elements Ri, unloading the data in the Ri, and continuing traversing the next level child node without rendering the corresponding point cloud data, and automatically supplementing the data to the Rn.
Preferably, the calculation node Bn has high calculation speed of the display size after being projected to the lens and the dynamic cut octree algorithm, and is suitable for being used in a low-calculation-force environment such as MR glasses; the dynamic scheduling process of the dynamic cutting octree algorithm has no influence on the real-time rendering efficiency, and the residual renderable data amount of each frame after cutting is controllable; the density distribution of the point cloud scene accords with the natural law observed by human eyes, and can be directly used for the exhibition application of massive digital achievements.
Preferably, the plurality of center points PBn and boundary points PEn which are dynamically scheduled and processed by the dynamic cut octree algorithm are copied into the MR glasses through cloud data, and the position and the gesture of the MR glasses in space can be accurately calculated through inertial navigation positioning in the copying process, so that real-time rendering of the digital point cloud scene can be accurately realized; the rendered physical scene is accurately overlapped with the physical scene seen in eyes, and scene navigation or data analysis and calculation work combining virtual and real are realized on the basis.
Preferably, an overall loading threshold value is required to be set in the dynamic scheduling process of the dynamic cut octree algorithm, if the point data which is loaded currently exceeds the threshold value, all other child node data are automatically shielded, new data are not loaded any more, and the dynamic scheduling display of massive digital point cloud data in the MR glasses can be realized through the setting of the parameters.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention uses the structure of the increment octree, can adopt the method of dynamic scheduling under CPU/GPU computing power and memory space of MR glasses, namely, calculate and load the visible child node data of the current field of view every frame, and unload the child node not already in the current field of view; therefore, CPU/GPU computing power and memory space of the MR glasses are fully utilized, and dynamic scheduling display of point cloud data is realized.
2. The dynamic cutting octree process used by the invention does not affect the real-time rendering efficiency, and the residual renderable data quantity of each frame after cutting is controllable; the density distribution of the point cloud scene accords with the natural law observed by human eyes, and can be directly used for the exhibition application of massive digital achievements.
Drawings
FIG. 1 is a flow chart of a method for dynamically scheduling and displaying massive digital point cloud data in MR glasses according to the invention
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a flow chart of a dynamic scheduling display method of massive digital point cloud data in MR glasses, and discloses a dynamic scheduling display method of massive digital point cloud data in MR glasses, which comprises the following steps: firstly, importing current view frame data into incremental octree data, traversing the incremental octree data, and calculating a central point P projected on a screen by coordinates of a certain level node Bn of a point cloud Bn Coordinates and pass through P Bn Calculating coordinates to obtain boundary point P En Coordinates; step two, dynamically scheduling by a dynamic cut octree algorithm, and calculating and loading a central point P of a current view child node Bn in each frame Bn Boundary point P En Unloading child nodes which are not in the current field of view, and obtaining a loading list An and An unloading list Rn; thirdly, after the loading list An is obtained, traversing the elements Ai in the loading list An, judging whether the elements Ai are loaded or not, and rendering corresponding point cloud data; step four, after obtaining an unloading list Rn, traversing elements Ri in the unloading list Rn, judging whether the current Ri is loaded or not, and unloading data in the Ri; step five, continuously traversing the next level of child nodes, and automatically supplementing the child nodes into Rn; and sixthly, returning to the first step, and continuing to execute the rendering of the next frame.
First, in a plurality of nodes Bn, according to the coordinates of a certain level of nodes Bn, calculating the center point P projected on the screen Bn The coordinate P ', the transformation formula of each point P to the screen coordinate P' is:
wherein: p is the coordinates of Bn; the posture matrix data M0 of the position of the person is obtained in real time through an inertial navigation positioning system; obtaining an internal reference matrix Mi and a perspective projection matrix Mp of the micro projector by using a calibration flow provided by the MR glasses; and calculating according to the current MR glasses display resolution to obtain a window transformation matrix Mw.
First step, through P Bn Calculating coordinates to obtain boundary point P En The coordinates and the calculation formula are as follows:
P En ＝P Bn +V 0 *R n
wherein: by means of a posture matrix M of the position of the person 0 Calculating to obtain the head top direction V of the person wearing the MR glasses 0 Then taking the radius R of the outside surrounding sphere of Bn n Calculating boundary point P En 。
The second step is that the dynamic scheduling method by the dynamic cutting octree algorithm comprises the following steps: firstly, judging the display size of a certain level of node Bn projected to a lens; then the central point P of a certain level node Bn is obtained Bn One boundary point P En And converts them into screen coordinate data; if P Bn And P En The coordinates are all outside the screen range, or P Bn And P En The distance value of the coordinates is smaller than a specified threshold L, and the current node and all child nodes are removed from the rendering queue; otherwise, displaying the point cloud content of the current node, continuously traversing the next level of child nodes, judging whether the current node can be displayed, putting the current node into a loading list An which can be displayed, and putting the current node into An unloading list Rn which cannot be displayed; the element in An is Ai and the element in Rn is Ri.
Thirdly, after the loading list An is obtained, traversing the elements Ai in the loading list An, and if the current Ai is already loaded, skipping the current elements Ai; if the current Ai is not loaded, loading the data request in the Ai, and rendering corresponding point cloud data.
And step four and step five, after obtaining an unloading list Rn, traversing the elements Ri in the unloading list Rn, if the current Ri is not loaded, skipping the current elements Ri, unloading the data in the Ri, continuing traversing the next level of child nodes without rendering the corresponding point cloud data, and automatically supplementing the child nodes into the Rn.
And sixthly, returning to the first step, and continuing to execute the rendering of the next frame.
The display size of the projected computing node Bn to the lens and the computing speed of the dynamic cut octree algorithm are high, and the method is suitable for being used in an environment with low computation power such as MR glasses; the dynamic scheduling process of the dynamic cutting octree algorithm has no influence on the real-time rendering efficiency, and the residual renderable data amount of each frame after cutting is controllable; the density distribution of the point cloud scene accords with the natural law observed by human eyes, and can be directly used for the exhibition application of massive digital achievements.
The central points PBn and the boundary points PEn which are dynamically scheduled by the dynamic cutting octree algorithm are copied into the MR glasses through cloud data, and the positions and the postures of the MR glasses in space can be accurately calculated through inertial navigation positioning, so that real-time rendering of the digital point cloud scene can be accurately realized; the rendered physical scene is accurately overlapped with the physical scene seen in eyes, and scene navigation or data analysis and calculation work combining virtual and real are realized on the basis.
And setting an overall loading threshold value in the dynamic scheduling process of the dynamic cutting octree algorithm, automatically shielding all other child node data if the currently loaded point data exceeds the threshold value, and not loading new data, thereby realizing the dynamic scheduling display of massive digital point cloud data in the MR glasses through the setting of the parameters.
Working principle:
1. starting rendering of the current frame;
2. judging the values of BPn and BEn according to the current view traversing increment octree data to obtain a loading list An and An unloading list Rn
3. IF (BPn and BEn are both out of view) {
The current child node Bn is added to Rn
}
4. ELSE IF (BPn and BEn are less than threshold L) { apart
The current child node Bn is added to Rn
}
5、ELSE{
The current child node Bn is added to An
Continuing traversing the child nodes of Bn
}
6. Element Ai { in FOR EACH An
7. IF (Ai has been loaded) { skip current element }
Loading the data request in Ai, and rendering corresponding point cloud data
}
8. The element Ri { in the FOR EACH Rn
9. IF Ri is not loaded { skip current element }
10. Unloading the data in Ri, and not rendering the corresponding point cloud data any more
12. Continuing traversing the next level of child nodes and automatically supplementing the child nodes into Rn
}
Returning to the step 1, continuing to execute the rendering of the next frame.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A dynamic scheduling display method of massive digital point cloud data in MR glasses is characterized by comprising the following steps:
the first step: importing the current view frame data into incremental octree data, traversing the incremental octree data, calculating the central point PBn coordinate of a certain level node Bn of the point cloud projected on a screen, and calculating the boundary point PEn coordinate through the PBn coordinate;
and a second step of: calculating and loading data of visible points of a central point PBn and a boundary point PEn of a current view child node Bn in each frame through dynamic scheduling of a dynamic cut octree algorithm, and unloading child nodes which are not in the current view to obtain a loading list An and An unloading list Rn;
and a third step of: after the loading list An is obtained, traversing the elements Ai in the loading list An, judging whether the elements Ai are loaded or not, and rendering corresponding point cloud data;
fourth step: after obtaining the unloading list Rn, traversing the elements Ri in the unloading list Rn, judging whether the current Ri is loaded or not, and unloading the data in the Ri;
fifth step: continuing traversing the next level of child nodes and automatically supplementing the child nodes into Rn;
sixth step: returning to the first step, and continuing to execute the rendering of the next frame;
the first step, in a plurality of nodes Bn, according to the coordinates of a certain level node Bn, calculates the center point P of the projection of the node Bn on the screen Bn The coordinate P ', the transformation formula of each point P to the screen coordinate P' is:wherein: p is the coordinates of Bn; the posture matrix data M0 of the position of the person is obtained in real time through an inertial navigation positioning system; obtaining an internal reference matrix M of the micro projector by using a calibration process provided by the MR glasses i And a perspective projection matrix M p The method comprises the steps of carrying out a first treatment on the surface of the Calculating to obtain a window transformation matrix M according to the current MR glasses display resolution w ，
The first step is performed by P Bn Calculating coordinates to obtain boundary point P En The coordinates and the calculation formula are as follows:
P En ＝P Bn +V 0 *R n
wherein: the head top direction V of the person wearing the MR glasses is calculated through the posture matrix M0 of the position of the person 0 Then taking the radius R of the outside surrounding sphere of Bn n Calculating boundary point P En 。
2. The method for dynamically scheduling and displaying massive digital point cloud data in MR glasses according to claim 1, wherein the dynamic scheduling method by dynamically cutting octree algorithm in the second step comprises: firstly, judging the display size of a certain level of node Bn projected to a lens; then, a central point PBn and a boundary point PEn of a certain level of node Bn are obtained, and are converted into screen coordinate data; if the PBn and PEn coordinates are both located outside the screen range, or the distance value of the PBn and PEn coordinates is smaller than a specified threshold L, the current node and all child nodes are removed from the rendering queue; otherwise, displaying the point cloud content of the current node, continuously traversing the next level of child nodes, judging whether the current node can be displayed, putting the current node into a loading list An which can be displayed, and putting the current node into An unloading list Rn which cannot be displayed; the element in An is Ai and the element in Rn is Ri.
3. The method for dynamically scheduling and displaying massive digital point cloud data in MR glasses according to claim 1, wherein the third step is to traverse the elements Ai in the loading list An after obtaining the loading list An, and skip the current elements Ai if the current Ai is already loaded; if the current Ai is not loaded, loading the data request in the Ai, and rendering corresponding point cloud data.
4. The method for dynamically scheduling and displaying massive digital point cloud data in MR glasses according to claim 1, wherein after obtaining an unloading list Rn, traversing elements Ri in the unloading list Rn, if current Ri is not loaded, skipping the current elements Ri, unloading data in Ri, continuing traversing the next level child node without rendering the corresponding point cloud data, and automatically supplementing to Rn.
5. The dynamic scheduling display method of massive digital point cloud data in MR glasses according to claim 1, wherein a plurality of center points PBn and boundary points PEn subjected to dynamic scheduling processing by a dynamic cutting octree algorithm are copied into the MR glasses through cloud data, and the position and the gesture of the MR glasses in space can be accurately calculated by inertial navigation positioning in the copying process.
6. The method for dynamically scheduling and displaying massive digital point cloud data in MR glasses according to claim 1, wherein an overall loading threshold is set in the dynamic scheduling process of the dynamic cut octree algorithm, and if the point data which is currently loaded exceeds the threshold, all other child node data are automatically shielded and new data are not loaded.
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| US9508186B2 (en) * | 2013-11-07 | 2016-11-29 | Autodesk, Inc. | Pre-segment point cloud data to run real-time shape extraction faster |
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