CN111462318A - Three-dimensional tree model real-time simplification method based on viewpoint mutual information - Google Patents
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Abstract
The invention discloses a three-dimensional tree model real-time simplification method based on viewpoint mutual information, which can enable trees in a forest scene to be rendered more smoothly and obtain better visualization effect.
Description
Technical Field
The invention belongs to the field of computer graphics and virtual geographic environments, and particularly relates to a three-dimensional tree model real-time simplifying method based on Viewpoint Mutual Information (VMI).
Background
At present, the three-dimensional tree model is simplified mainly by an image-based method and a geometric-based method. The Image-based rendering method (IBR) uses a two-dimensional Image of a tree to replace a geometric model for rendering, thereby significantly reducing the rendering load and improving the rendering efficiency. However, since the image is a two-dimensional object, this method has some inevitable disadvantages. Firstly, due to the limitation of image resolution, the method cannot be generally used for rendering of a close-range model, otherwise, strong non-photorealism is generated; secondly, the visualization effect of the method is static, and the dynamic illumination effect or the growth process simulation of the tree is difficult to perform; in addition, the IBR method mostly uses a single or several tree pictures to replace many trees, so the generated forest scene is often lack of diversity.
The simplified method based on geometry can be divided into simplification of a branch model and simplification of a leaf model according to different simplified objects, the branch is generally represented by a polygonal prism, the simplification mode of the branch is mostly reduced in complexity of the geometric primitives from the transverse direction and the longitudinal direction, most of the prior methods generate discrete L OD for the branch model, a large amount of data redundancy is generated, the problem is particularly serious for large-scale scenes, the simplified scheme aiming at the leaves is generally based on a random cutting mode, the simplified scheme of random cutting considers that all the leaves in the tree crown have the same importance degree, the simplified scheme of random cutting considers that a certain number of the leaves are randomly deleted when the tree crown is simplified, the visual information of the tree crown is still generated based on the visual information of the visual elements, and the simplified tree visual information is unreasonable when the simplified tree model is used for generating visual information of simplified tree trees.
Overall, the real-time simplification of current three-dimensional tree models presents a significant challenge: the order of leaf cutting is not considered, so that a low-quality visual effect is caused; the balance of effects and efficiency is not comprehensively considered, and the problems of serious visual jump, low performance and the like can be caused.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the defects of the existing three-dimensional tree model real-time simplification method in the aspects of visualization effect and rendering efficiency, the invention discloses a three-dimensional tree model real-time simplification method based on viewpoint mutual information, which can meet the requirements of visualization effect improvement and rendering efficiency improvement in a large-scale forest scene.
In order to achieve the purpose, the invention discloses a three-dimensional tree model real-time simplification method based on viewpoint mutual information, VMI is used for sorting leaves according to visual importance in preprocessing, a detail level model (L OD) is generated for the branches, optimization measures in a rendering process are combined, the number of DrawCall times is reduced by controlling L OD switching of nodes, the geometric size of the leaves is scaled in real time to reduce visual information loss caused by a simplification process, a crown visualization effect is expressed by a proper outline model in a long-range view, and the like, the rendering efficiency of a large-scale forest scene can be improved, and the visualization effect is improved, and the method comprises the following steps:
(1) dividing the tree into a plurality of nodes with parent-child relations according to the topological relation among the branches, wherein the nodes comprise branch nodes and tree leaf nodes, and the leaf nodes are child nodes of the final-stage branch nodes;
(2) calculating the visual importance of each leaf in the leaf node according to the viewpoint mutual information VMI, rearranging the vertex data of the leaves in the vertex array according to the visual importance, and placing more important data in front of the vertex array;
(3) simplifying the branch model according to the VMI to generate a detail level L OD model, and arranging vertex data in a vertex array according to the sequence of L OD models;
(4) in the real-time operation process, the simplification rate of the nodes is determined according to the tree crown bounding sphere level, the tree branch level, the leaf density, the distance between the viewpoint and the leaves and the included angle between the sight line and the growth direction of the branches;
(5) when a large-scale forest scene is rendered in real time, the adopted rendering optimization measures comprise controlling L OD change amplitude of a near node and L OD change frequency of a far node so as to reduce L OD switching, zooming the geometric size of leaves in real time so as to reduce visual information loss caused by a simplification process and ensure visual consistency among different L OD models of trees, and constructing a contour model expression crown model by using a Poisson surface reconstruction algorithm in a long-range view.
Further, the step (1) specifically comprises:
(1.1) recording the topological relation among branches and the length, the branch level and the leaf data information grown in the branches during tree modeling;
(1.2) constructing a structure data structure for each branch node, wherein the structure comprises the attribute information, the geometric information and the rendering state information of the node, and two dynamic arrays used for storing parent node and child node structure pointers respectively;
and (1.3) determining the pointers of the father node and the child nodes of the nodes according to the topological relation among the branches.
Further, the process of calculating the visual importance of the leaves according to the VMI in the step (2) is based on the nodes, and the specific steps are as follows:
(2.1) placing N around the treevEach viewpoint, all the viewpoint sets are V, and the V is used for indexing; if all the geometric patches in an object are collected as O, and O represents a single patch, then the overall visibility of the object O at a certain viewpoint v is:
where p (o | v) represents the conditional probability of visibility of the patch o at view point v, and p (o) represents the average visibility of the patch o at all view points, where node visibility is determined according to the fraction of pixels in screen space;
(2.2) when a node changes from O to O' due to the removal of a certain leaf, the VMI error caused by the change is:
if eVMIIf the size of the leaf is larger, the visibility of the leaf node O of the whole tree is influenced greatly visually by removing the leaf, so that the leaf is important in visual perception;
(2.3) according to eVMIThe size of the value of (a) can determine the visual importance of a certain leaf, and the leaves are sorted in the vertex array according to the visual importance, and the more important leaves are placed in front of the vertex array.
Further, a plurality of L OD models are generated for the branch model in the step (3), wherein the finer L OD model is constructed by adding some supplementary data on the basis of the coarse L OD model, the vertexes in the vertex array of the branch model are arranged according to the sequence of the L OD model, and the vertexes of the same L OD model are arranged together, and the L OD model to be rendered is determined according to different index arrays in the rendering process.
Further, the real-time simplification rate of the nodes in the step (4) is determined by five simplification rate influence factors, namely, the crown Bounding Sphere level (Bounding Sphere L eve, BS L), the Branch level (Branch L eve, B L), the leaf density (L eafDensity, L D), the distance (dist) between a viewpoint and a leaf, and the included angle (dir) between the sight line and the growth direction of the Branch, which are specifically described as follows:
the crown bounding sphere level BS L shows the degree of the nodes in the crown bounding sphere close to the center of the crown, and the nodes closer to the inside of the crown have higher BS L values and are more likely to be blocked by other nodes, so that the real-time reduction rate of the part of the nodes is higher relative to the nodes outside.
According to the branch level B L, observation key points of users browsing trees at a near place and a far place are not consistent, the users at the near place pay more attention to geometric details of the trees, and the users at the far place pay more attention to overall appearance characteristics of the trees, the invention utilizes B L parameters to adjust simplification strategies at different distances, and the specific operation is that a first-level branch model and a second-level branch model (B L is 1 and 2) can always reflect the overall outline of the trees, so that the simplification rate of the nodes is reduced when the distance is increased so as to reduce visual negative effects caused by excessive simplification, and the calculation formula is as follows:
wherein near and far represent the distance thresholds, max, for the finest and coarsest L OD, respectivelyBLRepresenting the maximum value of the B L parameter, and the parameter h is used to control f2(B L, dist) amplitude of variation with distance, parameter k1Guarantee f2(B L, dist) results were not less than-0.5.
Leaf density L D the present invention utilizes L D to ensure that sparse leaves are not overly simplified to maintain consistency of nodes between different L ODs, which is calculated as:
f3(LD)＝k2*(LD-ld)
where ld represents the average leaf density of all nodes, k2＝1/ld。
Distance dist between viewpoint and leaf: the influence of the distance parameter on the simplification rate is the most direct and greatest, and the calculation formula is defined as:
wherein k is3＝1/log10far. The logarithmic relationship of distance to reduction rate reduces the effect of distance at distance.
The included angle dir between the sight line and the growth direction of the branches: dir represents an included angle between the sight line direction and the growth direction of the node (for the leaf node, the parent node thereof), and the calculation formula is as follows:
the real-time simplification rate of the node is determined by the five functions, and the calculation formula is as follows:
Rs＝α1*f1(BSL)+α2*f2(BL，dist)+α3*f3(LD)+α4*f4(dist)+α5*f5(dir)
α therein1、α2、α3、α4、α5Equal to the weight of the impact factor and α1+α2+α3+α4+α5In the present invention, α4＝0.3，α2＝0.1，α1＝α3＝α5＝0.2。
Further, the multiple rendering optimization measures in the step (5) for rendering the large-scale forest scene specifically include:
distance-based L OD switching control only when the reduction rate change amount Δ rate and the time during which the reduction rate remains unchangedlastThe L OD of the node is updated when the following equations are satisfied;
wherein
k4、k5Are all larger than 0 and are respectively used for controlling the delta rate and the delta timelastIntensity as a function of distance;
maintaining the appearance characteristics of treesThe leaf amplification measures of (1): magnifying leaves by 1.0/(1-R) according to the change of simplification rate in a geometry shaders) Doubling to keep the total area of the leaves in the crown stable;
a contour model of the crown is constructed by utilizing a Poisson surface reconstruction algorithm, and the contour model is used for replacing a geometric model of a tree when a tree at a distance is rendered, so that the rendering burden is reduced.
The method has the advantages that the visual importance of the leaves is judged by calculating the average visibility of each leaf under multiple viewpoints in preprocessing, the sequence of cutting the leaves is more reasonable in the real-time simplification process, the tree simplification rate is effectively improved, meanwhile, the deformation of the tree is reduced, multiple influence factors are comprehensively considered in the real-time simplification process, the shielded part of the tree is effectively simplified, the tree simplification related to the viewpoints is realized, the continuous L OD effect in the browsing process is realized by combining the measure of dividing the tree into multiple nodes, the visual jump sense in the switching process of L OD is effectively reduced, and in addition, multiple optimization measures are provided for realizing the smooth rendering of large-scale forest scenes to realize the balance of efficiency and effect.
Drawings
Fig. 1 is a technical route diagram of the present invention.
FIG. 2 is a schematic diagram of a tree divided into a plurality of nodes; wherein: (a) dividing the tree into a plurality of nodes according to the topological relation among the branches; (b) parent-child relationships of nodes and corresponding data structures.
FIG. 3 is a diagram of L OD model of branch, where the numbers of edges corresponding to (a), (b), (c) and (d) are 12, 3 and 3, respectively, and the numbers of vertices are 18660, 5530, 928 and 530, respectively.
FIG. 4 is a schematic diagram of a process for constructing a tree profile model; wherein: (a) extracting characteristic points in the crown; (b) generating a closed contour model for the crown according to a Poisson surface reconstruction algorithm; (c) displaying the tree outline model in a wire frame mode; (d) and the data volume of the contour model is further reduced by using an edge folding algorithm.
FIG. 5 is a schematic view of leaves enlarged to maintain the overall appearance of the crown; wherein: (a) distances corresponding to (b) and (c) are respectively 5m, 30m and 100m, and the simplification rates are respectively 0%, 90% and 98%.
FIG. 6 shows a tree L OD model obtained by the method of the present invention, wherein the simplified rates of (a), (b), and (c) are 0%, 50%, and 98%, respectively.
FIG. 7 is a diagram of the visualization effect of a forest scene viewed from a distance rendered by the method of the present invention.
FIG. 8 is a visual effect diagram of a forest scene viewed from near, rendered by the method of the present invention.
Detailed Description
As shown in FIG. 1, the invention discloses a three-dimensional tree model real-time simplification method based on viewpoint mutual information, which mainly comprises the steps of dividing a tree into a plurality of nodes, sequencing leaves according to visual importance based on VMI, generating L OD models in an incremental form for branches, calculating real-time simplification rate for the nodes and optimizing measures in a rendering process.
1. And dividing the tree into a plurality of nodes with parent-child relations according to the topological relation among the branches.
When the tree model is established, attribute information such as branch length and branch level, geometric information such as vertex, normal and texture, rendering state information and topological relation of branches are recorded. As shown in fig. 2 (a), each branch is represented by a node, a secondary branch is derived from a primary branch, and a tertiary branch is derived from the secondary branch until the final branch is derived. The child nodes under the last branch include all leaves growing on the branch. The node data is organized in a multi-way tree, as in (b) of fig. 2. The tree data structure has the advantages that the information such as the simplification rate, the rendering state and the like of the child nodes can be conveniently controlled through the father node, and meanwhile, the DrawCall of the nodes can be merged during rendering, so that the process that a CPU sends data to a GPU is greatly reduced.
2. And judging the average visibility of the leaves under a plurality of visual angles according to the change of the VMI, and sequencing the leaves according to the average visibility.
Placing N around the treevAssuming that all viewpoints are set to be V (e.g., 20 viewpoints are placed around the tree and the viewpoints are located at 20 vertices on a regular dodecahedron completely surrounded by the tree), and V is an index, the set of object patches is set to be O, and O represents a single patch. a isoIs the projection area, a, of the patch o on a spherical surface with the viewpoint v as the center of the spheret＝∑o∈OaoWhen the sum of the projected areas of all patches at the viewpoint v is expressed, the conditional probability p (o | v) ═ a of the visibility of the patch o at the viewpoint vo/atFrom this, we derive the average visibility of patch o at all views as:
it should be noted that the projected area aoRefers to the portion of the projected area of patch o that is visible. If a patch o 'is completely occluded, the projected area of o' is 0. Finally, the definition of VMI can be derived as follows, which reflects the overall visibility of the object O at a certain viewpoint v.
VMI is very sensitive to geometric primitives outside the object, and compared with the occluded leaves inside, when the outer leaves are simplified, the VMI value changes more, so that the VMI can be used for measuring the visual importance degree of the leaves in the nodes. When a node changes from O to O' due to simplification, the VMI error introduced thereby is:
in the present invention, each leaf node is regarded as an independent object O, and each leaf is regarded as a patch O (actually containing two triangular meshes). The visual importance of each leaf is calculated in the pre-processing and the leaves are sorted accordingly. In the sorting process, e is selected each timeVMIThe largest leaf is the most important leaf. It should be noted that since the visibility of other leaves may be affected after one leaf is cut out, the calculation of VMI needs to be performed again each time one leaf is cut out. Finally, we will get all the leaf nodes that rank the leaves.
3. An L OD model in incremental form is generated for the branch model.
The branch model in the present invention is represented by polygonal prisms. Depending on the geometry of the prisms, the simplification of branches can be divided into three categories: transversely changing the number of the sides of the prism polygon; longitudinally combining branch segments; and removing small branch segments. The first method can effectively reduce the data volume of the branches without generating large deformation, but cannot be further simplified in the transverse direction when the prism is simplified into a triangular prism. When the distance between the viewpoint and the leaves is large, the detail of turning the branches does not need to be expressed too finely. By means of eVMIThe present invention can determine the degree of distortion before and after simplification of the merged two branch segments and determine the order of merging branch segments based thereon.furthermore, some smaller branches are too thin or too small to be viewed by the user.A removal of these branches is necessary.We use the magnitude of the Hausdorff distance to determine if a branch should be removed.A Hausdorff distance for a branch refers to the accumulated value of the distance of the branch node from its parent and siblings.A branch L OD construction process is shown in FIG. 3, where the number of edges in (a) - (d) in FIG. 3 are 12, 3, and the number of vertices are 18660, 5530, 928, 530, respectively.A and B in FIG. 3 are the branch segment merging process.A and B in FIG. 3 show how the number of polygon edges affects the data volume, and based on the two simplified methods above, the data volume is further reduced by removing the thinner branches, as shown in 3(c) and D in FIG. 3.
Compared with the initial L OD model of the branch, all tree L OD models do not generate new vertexes, and the refined L OD model can be constructed by adding some supplementary data on the basis of the coarse L OD model.
4. A real-time reduction rate is calculated for each node.
The real-time simplification rate of the nodes is determined by five simplification rate influence factors, namely a crown surrounding sphere level BS L, a branch level B L, leaf density L D, a distance dist between a viewpoint and leaves, and an included angle dir between a sight line and the growth direction of branches.
The specific introduction is as follows:
(4.1) crown sphere surrounding level BS L, representing the degree of nodes in the crown sphere surrounding sphere near the center of the crown, nodes closer to the inside of the crown have higher BS L values and are more likely to be blocked by other nodes, so the real-time reduction rate of the part of nodes is higher relative to the nodes outside.
(4.2) branch level B L, wherein the observation emphasis of a user is inconsistent when browsing the tree at a near place and a far place, the user pays more attention to the geometric details of the tree at the near place, and pays more attention to the overall appearance characteristics of the tree when observing the tree at the far place, the invention utilizes B L parameters to adjust the simplification strategy of different distances, and the specific operation is that for a first-level branch model and a second-level branch model (B L is 1 and 2), the simplification rate is gradually reduced and increased when the distance is increased, the calculation formula is as follows:
where near, far represent the corresponding distance thresholds, max, at the finest and coarsest L OD, respectivelyBLRepresenting the maximum value of the B L parameter, and the parameter h is used to control f2(B L, dist) amplitude of variation with distance, parameter k1Guarantee f2(B L, dist) results were not less than-0.5.
(4.3) leaf density L D the present invention utilizes L D to ensure sparse leaves are not overly simplified to maintain consistency of nodes between different L ODs, which is calculated as follows:
f3(LD)＝k2*(LD-ld)
where ld represents the average leaf density of all nodes, k21/ld. When leaf density is greater than ld, f3(L D) is positive number, the leaf density has promotion effect on simplification rate, and when the leaf density is less than ld, f3(L D) is positive, and leaf density is inhibitory to the reduction ratio.
(4.4) distance dist between viewpoint and leaf: the influence of the distance parameter on the simplification rate is the most direct and greatest, and the calculation formula is defined as follows:
wherein k is3＝1/log10far. The logarithmic relationship of distance to reduction rate reduces the effect of distance at distance.
(4.5) an included angle dir between the sight line and the growth direction of the branches: dir represents the angle between the sight line direction and the growth direction of the node (for the leaf node, the parent node thereof), and the calculation formula is as follows:
when dir is in [0, pi/2 ]]When the distance is within the range, the branch grows on the back of the crown with the viewpoint as a reference point and is shielded by the branch in front, and the larger the dir value is, the more serious the branch is shielded; when dir is in [ pi/2, pi]Within range, it is said that the branch grows on the front of the crown, so f is5The value of (dir) is 0.
The real-time simplification rate of the node is determined by the five functions, and the calculation formula is as follows:
Rs＝α1*f1(BSL)+α2*f2(BL，dist)+α3*f3(LD)+α4*f4(dist)+α5*f5(dir)
α therein1、α2Equal to the weight of the impact factor and α1+α2+α3+α4+α5Considering that the distance has the greatest influence on the reduction ratio, α is assumed in the present invention4＝0.3，α2＝0.1，α1＝α3＝α5＝0.2。
5. And optimizing the visualization effect and efficiency when rendering the large-scale forest scene.
In order to realize the efficient rendering of the large-scale forest scene, the invention adopts various optimization measures during rendering, and the specific introduction is as follows:
and (5.1) replacing the tree outline model when rendering the distant trees. The steps of constructing the tree profile model are shown in fig. 4: firstly, selecting top end points of all branches as feature points, setting a distance threshold value theta as shown in (b) in fig. 4, and deleting all end points with the distance to the center of the crown smaller than theta; then, a tree crown contour model is generated by using a poisson surface reconstruction method, as shown in (c) of fig. 4. The generated crown model can show the whole contour of the crown in a real way; finally, the number of vertices is further compressed by edge folding, and the final result is shown as (d) in fig. 4. Compared with 310364 vertices in the original crown model, the crown contour model constructed finally has only 744 vertices. By the method, the burden and the frequency of DrawCall can be obviously rendered, and the rendering efficiency of the large-scale forest scene is greatly improved.
(5.2) distance-based L OD switching control.nearby nodes tend to occupy more pixels on the screen due to being closer to the camera, so their L OD changes should not be too severe, otherwise a strong sense of jump will result, while for distant nodes, their L OD changes are less noticeable by the viewer due to being further away and heavily occluded.A L OD does not need to change too frequently for these nodes.A frequency and magnitude of their L OD changes are closely related to the distance for both the nearby and distant nodesThe node records the change of its reduction rate Δ rate and the time during which the reduction rate remains unchangedlast. Only when Δ rate and timelastThe L OD of the node will be updated when the following equation is satisfied.
Here, the
k4、k5Are all larger than 0 and are respectively used for controlling the delta rate and the delta timelastBy the method, unnecessary L OD switching is effectively reduced, and rendering efficiency is greatly improved.
(5.3) altering the position of the leaf vertex in the geometry shader to enlarge the leaf to maintain the overall appearance of the crown. For node i, assuming that the number of leaves in the initial state is n, the total area of all leaves is S, the reduction rate is 0.0, and when the reduction rate becomes R at a certain timesMeaning that there will be n RsThe leaves of the leaf will be cut out, and the total area of the leaves can be approximately expressed as:
a′total＝(1-Rs)*atotal
the reduction of the leaf area causes a certain loss of visual quality, and in order to compensate for the deformation of the node caused by simplification, the invention expands the remaining leaves outwards by s times along the center of each leaf, and at the moment, the total area of the node becomes:
a′total＝s2*(1-Rs)*atotal，s＝sqrt(1.0/(1-Rs))
the effect of enlarging the tree leaf is shown in fig. 5, (a), (b), and (c) in fig. 5 show L OD models with distances between the tree and the viewpoint of 5m, 30m, and 100m, respectively, and the corresponding simplification rates are 0%, 90%, and 98%, respectively, from which it can be seen that even if the simplification rate of the tree model reaches 98%, the overall appearance characteristics of the tree are well maintained by virtue of the leaf enlargement scheme provided by the present invention.
FIG. 6 shows a L OD model diagram generated by the present invention, in which the simplification rates of (a), (b) and (c) are 0%, 50% and 98%, respectively, the tree species is a quercus robur tree, which contains 133327 triangle primitives.
Fig. 7 and 8 are respectively a visualization effect diagram of browsing in a large-scale forest scene by using the invention, wherein fig. 7 is browsing in a forest far away, and fig. 8 is roaming in the forest. The scene contains 2000 trees in total, and the number of triangle primitives is over 2 hundred million in the initial state. In the view frustum shown in fig. 7, there are 621 trees in total, 540 triangle primitives, the average simplification rate is 9.13%, and the real-time frame rate is 40.21 fps. In the view frustum shown in fig. 8, there are 403 trees, 37 ten thousand triangle primitives, the average reduction rate is 10.57, and the real-time frame rate is 52.41 fps. It can be seen that, no matter far-away browsing or near-around roaming, the tree simplification method and the optimization measure provided by the invention can achieve very smooth rendering and better visualization effect on large-scale forest scene rendering.
Claims (6)
1. A three-dimensional tree model real-time simplification method based on viewpoint mutual information is characterized by comprising the following steps:
(1) dividing the tree into a plurality of nodes with parent-child relations according to the topological relation among the branches, wherein the nodes comprise branch nodes and tree leaf nodes, and the leaf nodes are child nodes of the final-stage branch nodes;
(2) calculating the visual importance of each leaf in the leaf node according to the viewpoint mutual information VMI, rearranging the vertex data of the leaves in the vertex array according to the visual importance, and placing more important data in front of the vertex array;
(3) simplifying the branch model according to the VMI to generate a detail level L OD model, and arranging vertex data in a vertex array according to the sequence of L OD models;
(4) in the real-time operation process, the simplification rate of the nodes is determined according to the tree crown bounding sphere level, the tree branch level, the leaf density, the distance between the viewpoint and the leaves and the included angle between the sight line and the growth direction of the branches;
(5) when a large-scale forest scene is rendered in real time, the adopted rendering optimization measures comprise controlling L OD change amplitude of a near node and L OD change frequency of a far node so as to reduce L OD switching, zooming the geometric size of leaves in real time so as to reduce visual information loss caused by a simplification process and ensure visual consistency among different L OD models of trees, and constructing a contour model expression crown model by using a Poisson surface reconstruction algorithm in a long-range view.
2. The method for simplifying the three-dimensional tree model based on the viewpoint mutual information in real time as claimed in claim 1, wherein the step (1) specifically comprises:
(1.1) recording the topological relation among branches and the length, the branch level and the leaf data information grown in the branches during tree modeling;
(1.2) constructing a structure data structure for each branch node, wherein the structure comprises the attribute information, the geometric information and the rendering state information of the node, and two dynamic arrays used for storing parent node and child node structure pointers respectively;
and (1.3) determining the pointers of the father node and the child nodes of the nodes according to the topological relation among the branches.
3. The method for simplifying the three-dimensional tree model based on the viewpoint mutual information in real time as claimed in claim 1, wherein the step (2) of calculating the visual importance of the leaves according to the VMI is performed in a screen space, and the nodes are independent of each other, and the specific steps include:
(2.1) placing N around the treevEach viewpoint, all the viewpoint sets are V, and the V is used for indexing; a certainIf all the geometric patches in an object are collected as O, and O represents a single patch, then the overall visibility of the object O at a certain viewpoint v is:
where p (o | v) represents the conditional probability of visibility of the patch o at view point v, and p (o) represents the average visibility of the patch o at all view points, where node visibility is determined according to the fraction of pixels in screen space;
(2.2) when a node changes from O to O' due to the removal of a certain leaf, the VMI error caused by the change is:
if eVMIIf the size of the leaf is larger, the visibility of the leaf node O of the whole tree is influenced greatly visually by removing the leaf, so that the leaf is important in visual perception;
(2.3) according to eVMIThe magnitude of the value of (a) determines the visual importance of a leaf, and accordingly ranks the leaves in the vertex array, with more important leaves being placed in front of the vertex array.
4. The method for real-time simplification of three-dimensional tree models based on viewpoint mutual information as claimed in claim 1, wherein in step (3), a plurality of L OD models are generated for the branch models, wherein the finer L OD model is constructed by adding some supplementary data on the basis of the coarse L OD model, the vertices are arranged in the vertex array of the branch model according to the order of the L OD models, and the vertices of the same L OD model are arranged together, and the L OD model to be rendered is determined according to different index arrays in the rendering process.
5. The real-time simplification method of three-dimensional tree model based on viewpoint mutual information as claimed in claim 1, wherein the real-time simplification rate of the nodes in step (4) is determined by five simplification rate influence factors, including the crown bounding sphere level BS L, the branch level B L, the leaf density L D, the distance dist between the viewpoint and the leaf, and the included angle dir between the sight line and the branch growth direction, the corresponding function calculations are as follows:
the corresponding calculation formula of the BS L is:
the corresponding calculation formula of B L is:
wherein near and far represent the distance thresholds, max, for the finest and coarsest L OD, respectivelyBLRepresenting the maximum value of the B L parameter, and the parameter h is used to control f2(B L, dist) amplitude of variation with distance, parameter k1Guarantee f2(B L, dist) result not less than-0.5;
l D is calculated according to the following formula:
f3(LD)＝k2*(LD-ld)
where ld represents the average leaf density, k, of all nodes in the initial state2＝1/ld；
The corresponding calculation formula of dist is:
wherein k is3＝1/log10(far-near+1)；
The calculation formula corresponding to dir is as follows:
real-time reduction rate R of nodessDetermined by the five functions, the calculation formula is as follows:
Rs＝α1*f1(BSL)+α2*f2(BL,dist)+α3*f3(LD)+α4*f4(dist)+α5*f5(dir)
α therein1、α2、α3、α4、α5Represents the weight of the influence factor and α1+α2+α3+α4+α5＝1。
6. The method for simplifying the three-dimensional tree model based on the viewpoint mutual information in real time as claimed in claim 1, wherein the step (5) comprises a plurality of rendering optimization measures during rendering of the large-scale forest scene, specifically comprising:
distance-based L OD switching control only when the reduction rate change amount Δ rate and the time during which the reduction rate remains unchangedlastThe L OD of the node is updated when the following equations are satisfied;
wherein
near and far represent distance thresholds, k, for finest and coarsest L OD, respectively4、k5Are all larger than 0 and are respectively used for controlling the delta rate and the delta timelastIntensity as a function of distance;
leaf amplification measures for maintaining appearance characteristics of trees: according to a reduction ratio R in a geometry shadersThe change of (a) amplifies the leaves by 1.0/(1-R)s) Doubling to keep the total area of the leaves in the crown stable;
a contour model of the crown is constructed by utilizing a Poisson surface reconstruction algorithm, and the contour model is used for replacing a geometric model of a tree when a tree at a distance is rendered, so that the rendering burden is reduced.
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