CN113032885B - Vision relation analysis method, device and computer storage medium - Google Patents

Vision relation analysis method, device and computer storage medium Download PDF

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CN113032885B
CN113032885B CN202110376074.5A CN202110376074A CN113032885B CN 113032885 B CN113032885 B CN 113032885B CN 202110376074 A CN202110376074 A CN 202110376074A CN 113032885 B CN113032885 B CN 113032885B
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CN113032885A (en
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王浩锋
金珊
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Shenzhen University
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Abstract

The invention discloses a visual field relation analysis method, equipment and a computer storage medium, wherein the method comprises the following steps: generating reachable relation data and visible relation data of each grid in the building plan; calculating the average visible depth and the average observed depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid; the invention solves the problem that the analysis method for splitting the two space experience modes of motion and vision in the prior art cannot truly describe the motion perception experience of classical gardens in China and the space characteristics of 'seen' and 'seen' of scenes, and better reveals the space perception characteristics of different parts of classical gardens in China through the quantitative analysis method for 'seen' and 'seen' space experience.

Description

Vision relation analysis method, device and computer storage medium
Technical Field
The present invention relates to analysis of classical garden and visual field relation, and more particularly, to a visual field relation analysis method, apparatus and computer storage medium.
Background
In a typical building, the visual and reachable relationships are almost identical, i.e., the places that can be seen mostly go directly past. However, the space of classical gardens in China has the phenomenon of separating and misplacing the common accessibility from the visual relationship, namely the places where the sight is located cannot be directly reached, and the places often need to be reached through a tortuous path. The asymmetry of the reachable and visible relationships brings about a unique "seen" and "seen" spatial experience for classical gardens: some places are easy to walk through and have good vision, and other places are not easy to walk through but are easy to see. For this experience, most studies are only described by literature language or photo-schematic, and cannot be objectively described from a quantitative perspective.
While visual relationship analysis (VGA: visibility Graph Analysis) of Space Syntax theory attempts to simulate visual relationship changes in motion through successive descriptions of visual fields, current methods are largely incapable of classical garden accessibility with spatial systems that have significant misalignments from visual relationships. Thus, in application, these two relationships have to be fractured, and "sports and vision" are separately modeled as two independent systems: one is the reachable layer view model and the other is the visual layer view model. The visual relationship of the real reaction space is difficult to realize by single visual analysis or reachable analysis, namely, the single visual analysis ignores the obstacle of a transparent wall body (such as a window and the like) or a short obstacle to movement, so that the visual degree of the space is overestimated, and a person cannot 'fly' from one position to move to other positions to watch other invisible places; the simple reachable analysis is that the transparent boundary is not different from the solid boundary, and the analysis result is inevitably underestimated in space visibility due to the fact that the effect of 'sight line advance' is not considered.
The method for manually splitting the two space experience modes of motion and vision naturally cannot truly describe the motion perception experience of classical gardens of China and the space characteristics of 'seeing' and 'seen' of scenes. Therefore, there are many limitations in practical application, and it is difficult to cope with analysis of complex space.
Disclosure of Invention
In view of this, the embodiments of the present application provide a visual field relationship analysis method, apparatus, and computer storage medium, which solve the problem that in the prior art, the analysis method of splitting two spatial experience modes of motion and vision cannot truly describe the motion perception experience of classical gardens in China and the spatial characteristics of "seeing" and "seen" of scenes.
The embodiment of the application provides a visual field relation analysis method, which comprises the following steps:
generating reachable relation data and visible relation data of each grid in the building plan;
and calculating the average visible depth and the average observed depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid.
In an embodiment, the generating the reachable relational data and the visual relational data of each grid in the building plane includes:
Obtaining a building plan;
drawing the building plan into a space syntactic analysis base map, and dividing the space syntactic analysis base map into a first number of grids with equal size;
based on the space syntactic analysis base map, storing the reachable attribute data of each grid into a first data table in turn according to the serial number sequence of the grids, and generating a reachable layer space relation graphic data table;
and based on the space syntactic analysis base map, sequentially storing the visual attribute data of each grid into a second data table according to the serial number sequence of the grids, and generating a visual layer space relation graphic data table.
In an embodiment, the calculating the average visual depth and the average perceived depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid includes:
acquiring an reachable grid matrix and a visible grid matrix of each grid through the serial number of the grid based on the reachable layer space relation graphic data table and the visible layer space relation graphic data table;
calculating the average visible depth of each grid by using a first preset method based on the reachable grid matrix and the visible grid matrix;
And calculating the average perceived depth of each grid by using a second preset method based on the reachable grid matrix and the visible grid matrix.
In an embodiment, the calculating, based on the reachable grid matrix and the visible grid matrix, an average visible depth of each grid by using a first preset method includes:
selecting a starting point grid, wherein the number of visible grids corresponding to the starting point grid is V 0 The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the starting point grid is any grid in the space syntactic analysis base graph;
starting from the starting point grid, executing a first reachable topology, and obtaining a direct reachable grid of the first reachable topology and the direct reachable grid corresponding to each otherIs recorded as the number V of new visible grids of the first reachable topology 1
Starting from any newly added visible grid of the last reachable topology, executing the ith reachable topology, obtaining the total number of directly reachable grids of the ith reachable topology and the directly reachable grids corresponding to the directly reachable grids, and recording the total number as the newly added visible grid number V of the ith reachable topology i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i is a positive integer;
repeatedly executing the operation until the number of the visible grids of the starting point grids reaches the total number of grids minus 1, and stopping topology operation; wherein the total grid number is the first number;
Based on the number V of the visible grids corresponding to the starting grid 0 Current reachable topology depth i, newly added number of visible grids V of the ith reachable topology i And carrying out total times of the reachable topology and total grid quantity, and calculating the average visible depth of the starting point grid.
In an embodiment, the average visual depth of each grid is an average topological depth at which any one starting grid in the spatial syntactic analysis base is reachable or at which other grids are visible.
In an embodiment, the calculating, based on the reachable grid matrix and the visible grid matrix, an average depth of view of each grid by using a second preset method includes:
the first number of grids is taken as targets, grids of the direct visual starting point grids are obtained and marked as visual grid areas, and the number of grids of the visual grid areas is D 0
Removing grids of the visible grid area from the first number of grids to obtain remaining grids;
executing a first reachable topology in the remaining grids, obtaining the number of grids in the remaining grids, which can reach the visible grid area, and recording as the newly increased reachable grid number D of the first reachable topology 1
Adding the newly added reachable grid obtained by the last reachable topology into the visible grid area to generate a new visible grid area;
removing the new visible grid area from the remaining grids to obtain new remaining grids;
executing the ith reachable topology in the new remaining grids to obtain the number of grids in the new remaining grids, which can reach the new visible grid area, and recording as the newly increased number of reachable grids D of the ith reachable topology i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i is a positive integer;
repeating the operation until the new number of the remaining grids is reduced to zero, and stopping topology operation;
grid number D based on the visual grid area 0 Current reachable topology depth i, newly added reachable grid number D of the ith reachable topology i And carrying out the total times of the reachable topology and the total grid number, and calculating the average depth of view of the starting point grid.
In an embodiment, the average perceived depth of each grid is the average topological depth of any grid reachable or visible starting grid in the spatial syntactic analysis base.
In an embodiment, the method further comprises:
based on the analysis result of the view relationship of each grid, a visualization operation is performed.
In order to achieve the above object, there is also provided a computer storage medium having stored thereon a program of a visual field relation analysis method, which when executed by a processor, implements the steps of any one of the visual field relation analysis methods described above.
In order to achieve the above object, there is also provided a visual relationship analysis apparatus including a memory, a processor and a program of a visual relationship analysis method stored on the memory and executable on the processor, the processor implementing the steps of any one of the above visual relationship analysis methods when executing the program of the visual relationship analysis method.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
generating reachable relation data and visible relation data of each grid in the building plan; through calculation of software, accurate reachable relation data and visible relation data of each grid in the building plan are generated, and accuracy of average visible depth and average visible depth of each grid in subsequent calculation is guaranteed;
calculating the average visible depth and the average observed depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid; in the accessible space of the building area, i.e. the space accessible to humans (the range defined by the accessible layer), other spaces are excluded; the definition herein avoids increasing the amount of space (number of grids of the plane) of the model, thereby avoiding the mathematical errors caused by the skew of the data distribution; and precisely carrying out relation analysis on each grid through quantized average visual depth and average visual depth, thereby revealing the spatial characteristics of the building.
The method solves the problem that the analysis method for splitting the two space experience modes of motion and vision in the prior art cannot truly describe the motion perception experience of classical gardens in China and the space characteristics of 'seeing' and 'seeing' of scenes, and better reveals the space perception characteristics of different parts of classical gardens in China through the quantitative analysis method for 'seeing' and 'seeing' space experiences.
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FIG. 1 is a flow chart of a first embodiment of a visual field relationship analysis method of the present application;
fig. 2 is a schematic flowchart of step S110 in the first embodiment of the view relationship analysis method of the present application;
FIG. 3 is a plan view of an example network teacher's garden and corresponding reachable layer bottom and visual layer bottom;
fig. 4 is a schematic flowchart of step S120 in the first embodiment of the view relationship analysis method of the present application;
fig. 5 is a schematic diagram of a specific flow of step S122 of the view relationship analysis method of the present application;
FIG. 6 is a schematic diagram of the measurement method of "seen" (left image) and "seen" (right image) in the view relationship analysis method of the present application
Fig. 7 is a schematic diagram of a specific flow of step S123 of the visual field relationship analysis method of the present application;
FIG. 8 is a flow chart of a second embodiment of a visual field relationship analysis method of the present application;
FIG. 9 is a schematic diagram comparing the analysis results of the prior art and the present method;
fig. 10 is a schematic diagram of a hardware architecture of a view relationship analysis device according to an embodiment of the present application;
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The main solutions of the embodiments of the present invention are: generating reachable relation data and visible relation data of each grid in the building plan; calculating the average visible depth and the average observed depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid; the invention solves the problem that the analysis method for splitting the two space experience modes of motion and vision in the prior art cannot truly describe the motion perception experience of classical gardens in China and the space characteristics of 'seen' and 'seen' of scenes, and better reveals the space perception characteristics of different parts of classical gardens in China through the quantitative analysis method for 'seen' and 'seen' space experience.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
Referring to fig. 1, fig. 1 is a first embodiment of a visual field relation analysis method of the present application, the method includes:
step S110: reachable relational data and visual relational data for each grid in the building plan are generated.
Specifically, the reachable relational data and the visual relational data of each grid in the building plan can be generated by a preset method, wherein the preset method can be to use related software, and in the embodiment, the space syntax analysis base map can be generated by CAD software or other methods; the grid is generated, and the reachable relation diagram data table and the visible relation diagram data table are generated by using DepthmapX software.
In particular, the reachability relationship data may be a reachability layer spatial relationship schema data table; the visual relationship data may be a visual layer spatial relationship schema data table; the present invention is not limited to the above data table, and may include other data of a visual or reachable relationship.
Step S120: and calculating the average visible depth and the average observed depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid.
Specifically, in this embodiment, the accessible space of the building plan includes only the space accessible to a person, i.e., the range defined by the accessible layer, and other spaces are excluded; the definition herein can avoid increasing the number of spatial quantities (number of grids of the plane) of the model, thereby reducing errors; since the calculation of the average topology depth is significantly affected by the amount of space, and thus may be subject to statistical errors due to skewing of the data distribution.
Specifically, analyzing the average perceived depth and the average perceived depth of each grid generated may better measure the "deep" and "shallow" of the visual relationship.
Specifically, a visual field relation analysis (VGA: visibility Graph Analysis) method of Space Syntax (Space Syntax) theory is an important technical means of spatial research in the field of architecture, and forms a series of computer software tools, such as DepthmapX, isovist, decodingspace Toolbox, syntax2D, and the like. Taking the most influential space syntax software DepthmapX as an example, the method covers the analyzed building plane with a uniform grid with a certain density, and draws an equal view map (Isovists, namely the view area range seen from 360 degrees of the point and the morphological constitution attribute of a view polygon formed by the shielding of a wall body) of each grid (center point); in addition to measuring the geometric attributes of the views, the degree of overlapping of the views and the topological Depth change of the visual relationship between the grids are measured by indexes such as Connectivity (Connectivity) and average Depth (Mean Depth). The shape and the size of the equal vision field are changed along with the different observation points in the building plane, which reflects the vision field change experienced by people in the movement process. A series of successive equal views form a continuous scene, representing a scene such as a walk in a building. A large number of demonstration researches at home and abroad reveal that the visual field topological connection mode of the building layout influences the cognitive process and behavior of people, such as line organization or static space occupation mode.
In the above embodiment, the following beneficial effects exist: by quantifying the average visible depth and the average visible depth of each grid, the space experience of 'seeing' and 'seen' is more obvious, and the space experience characteristics and differences of 'seeing' and 'seen' of a complex building space (such as classical gardens) are quantitatively described, so that the space design method of the classical gardens is better understood, and the space perception characteristics of different parts of the classical gardens of China are better revealed.
Referring to fig. 2, fig. 2 is a specific implementation step of step S110 in the first embodiment of the view relationship analysis method of the present application, where the generating the reachable relationship data and the visible relationship data of each grid in the building plane includes:
step S111: a building plan is obtained.
Specifically, the building plan can be simply called as a plan, which is a drawing formed by a horizontal projection method and corresponding legends according to the building conditions such as walls, doors and windows, stairs, floors, internal functional layouts and the like of a newly built building or a structure.
In the present application, a garden plan (jpg or vector map, please ensure that the plane has a scale or a drawing unit) is taken as a main study object, but the present invention is not limited to a garden plan, and is applicable to a complex building space including a combination of an accessible space and a visible space. In this application, specific examples are described using a cyber garden in su state gardens as an example, but the method is not limited to the cyber garden.
Step S112: the building plan is drawn as a spatially syntactic base and the spatially syntactic base is divided into a first number of equal-sized grids.
Specifically, installing CAD software of a Windows system and DepthmapX (the latest version of DepthmapX is v 0.8); introducing jpg pictures or vector mapping pictures of the network teacher garden plan into CAD drawing software such as Autocad, and then drawing a space syntax VGA analysis base map; in the drawing, two classes of boundaries in a plane are distinguished: visual boundaries and reachable boundaries. Visual boundaries refer to opaque entities such as walls above eye height that block vision; accessible boundaries refer to boundaries that block movement of the human body, including, in addition to the former, some boundaries that are low in height (below Eye level) or transparent, such as rails, greening, water, landing glass, etc. (fig. 3, left side of the drawing in fig. 3 is a net-garden plan view, right side of the drawing is a foot-height accessible layer VGA base (drawn according to building plane boundary conditions of human foot height (Eye-level)), and right side of the drawing is a foot-height accessible layer VGA (drawn according to boundary conditions of human Eye height (Eye-level)). Referring to the description of the fourth chapter of the thirteenth and fifteen planning teaching materials of the Ministry of construction, the Visual boundary and the reachable boundary are respectively drawn on two layers (such as the Visual boundary and the Access boundary respectively named), the peripheral boundary of each layer is ensured to be closed, and then the drawn graph is stored as a dxf file format.
Step S113: and based on the space syntactic analysis base map, storing the reachable attribute data of each grid into a first data table in sequence according to the serial number sequence of the grids, and generating a reachable layer space relation graphic data table.
Specifically, the previously stored dxf file is imported into the DepthmapX. Ensuring that both the reachable Layers and the visible Layers in the draging Layers are in an open state. Referring to the description of chapter 4.2.2 of the space syntax course, the VGA analysis grid size is set to 0.6 meters, the range of the reachable space is filled, and the space relation diagram of the reachable layer is generated. Then, the spatial relationship diagram of the reachable layers is output as a CSV file, and the menu path of DepthmapX is: map→export→ Visibility Graph Connections as CSV …. The output CSV file stores information of other grids directly connected with each grid in a grid ID numbering mode, and for convenience of distinguishing, the file can be named as ' Access links ' CSV '.
In particular, the reachable properties data may include reachable grid matrix, connection relation, average depth, and the like, which are not limited herein.
Step S114: and based on the space syntactic analysis base map, sequentially storing the visual attribute data of each grid into a second data table according to the serial number sequence of the grids, and generating a visual layer space relation graphic data table.
Specifically, the previously stored dxf file is imported into the DepthmapX. Ensuring that both the reachable Layers and the visible Layers in the draging Layers are in an open state. And referring to the description of the fourth chapter 4.3.2 of the space syntax course, switching to a draging Layers as a current working layer, closing the reachable layer of the imported dxf file, ensuring that only the visible layer is in an open state, and then regenerating a spatial relationship diagram, namely the relationship diagram of the visible layer. Then, the spatial relation diagram of the visual layers is output as a CSV file, and the menu path of the DepthmapX is shown as above; for ease of distinction, the data table of the visual layer may be named "VisibilityLinks. Csv".
In particular, the visual attribute data may include a visual grid matrix, a connection relationship, an average depth, and the like, which are not limited herein.
In the above embodiment, the following beneficial effects exist: through the steps, the reachable layer space relation graphic data table and the visible layer space relation graphic data table are correctly generated, so that the accuracy of calculation of the average visible depth and the average perceived depth of the subsequent grids is ensured, and the spatial characteristics of the building gardens are ensured to be correctly analyzed.
Referring to fig. 4, fig. 4 is a specific implementation step of step S120 in the first embodiment of the view relationship analysis method of the present application, where the calculating, based on the reachable space of the building plan, the average visual depth and the average perceived depth of each grid according to the reachable relationship data and the visual relationship data, to complete the view relationship analysis of each grid includes:
step S121: and acquiring the reachable grid matrix and the visible grid matrix of each grid through the serial numbers of the grids based on the reachable layer space relation graphic data table and the visible layer space relation graphic data table.
Specifically, in the process of generating the reachable layer space relation graphic data table and the visible layer relation graphic data table, the positions of grids are not changed, the numbers of the grids in the two layers are identical, and the space in the same position obtains the visible attribute data and the reachable attribute data.
Step S122: and calculating the average visual depth of each grid by using a first preset method based on the reachable grid matrix and the visual grid matrix.
Specifically, in the present embodiment, the average visual depth of each grid is calculated by the c++ language, and the calculation result is stored as txt file, but the present invention is not limited to the above language and the above file storage method, and may be dynamically adjusted according to the requirement.
Step S123: and calculating the average perceived depth of each grid by using a second preset method based on the reachable grid matrix and the visible grid matrix.
Specifically, the description in step S122 is already provided, and will not be repeated here.
In the above embodiment, the following beneficial effects exist: the average visible depth and the average visible depth of each grid are calculated correctly through the first preset method and the second preset method, so that the spatial information of each grid can be analyzed accurately.
Referring to fig. 5, fig. 5 is a specific implementation step of step S122 in the view relationship analysis method of the present application, where calculating, based on the reachable grid matrix and the visible grid matrix, an average visible depth of each grid by using a first preset method includes:
step S1221: selecting a starting point grid, wherein the number of visible grids corresponding to the starting point grid is V 0 The method comprises the steps of carrying out a first treatment on the surface of the The starting point grid is any grid in the space syntactic analysis base graph.
Step S1222: starting from the starting point grid, executing a first reachable topology, obtaining the total number of directly reachable grids of the first reachable topology and the directly reachable grids corresponding to the directly reachable grids, and recording the total number as the newly increased number V of the directly reachable grids of the first reachable topology 1
Step S1223: starting from any newly added visible grid of the last reachable topology, executing the ith reachable topology, obtaining the total number of directly reachable grids of the ith reachable topology and the directly reachable grids corresponding to the directly reachable grids, and recording the total number as the newly added visible grid number V of the ith reachable topology i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i is a positive integer.
Step S1224: repeatedly executing the operation until the number of the visible grids of the starting point grids reaches the total number of grids minus 1, and stopping topology operation; wherein the total grid number is the first number.
Step S1225: based on the number V of the visible grids corresponding to the starting grid 0 Current reachable topology depth i, newly added number of visible grids V of the ith reachable topology i And carrying out total times of the reachable topology and total grid quantity, and calculating the average visible depth of the starting point grid.
Specifically, the topological depth algorithm (average visual depth) of "view analysis" is as follows:
Figure BDA0003010154050000101
Figure BDA0003010154050000111
the calculation thought of the codes is as follows:
and (3) performing reachable topology on the current visible grid set of the starting grid, wherein each topology adds a new visible grid until the number of visible grids of the starting grid reaches (the total grid number-1).
Setting the current reachable topology depth as i, and newly increasing the number V of visible grids of the ith reachable topology i The total number of times of topology is reached is n, and the number of visible grids at the starting grid is V 0 If the total grid number is C, the calculation formula of the average visual depth is:
Figure BDA0003010154050000112
the specific steps of the algorithm code are as follows:
1) Starting from a starting point grid, making a first reachable topology, directly reachable grids of the first reachable topology and the total number of grids directly viewable by the reachable grids, and recording as the newly increased number V of visible grids of the first topology 1
2) Starting from the visible grids of the first topology, making a second reachable topology, directly reachable grid data of the current topology and the total number of the grids directly visible by the reachable grids, and subtracting the visible grid number V of the last reachable topology 1 Obtaining the newly increased visible grid number V of the secondary topology 2
3) Starting from the visible grids of the second topology, making a third reachable topology, directly reachable grid data of the current topology and the total number of the grids directly visible by the reachable grids, and subtracting the visible grid number V of the last reachable topology 2 Obtaining the newly increased visible grid number V of the secondary topology 3
4) And analogizing is performed until the number of the visible grids of the starting point grids reaches the total number of grids in the map, and the topology stops;
5) According to equation 1, the average visual topological depth of the starting grid is calculated.
In the above embodiment, the following beneficial effects exist: the correct calculation of the average visual depth of each grid is guaranteed, thereby better quantifying the "seen" spatial experience.
In one embodiment, the average visual depth of each grid is the average topological depth of any starting grid reachable or visible other grids in the space syntactic analysis base.
Specifically, referring to the left diagram of fig. 6, a schematic diagram of a method for measuring an average visual topological depth of a point J is shown, taking the left diagram of fig. 6 as an example, where the point J "sees" the average topological depth:
depth 1 (visible): 1080 grids;
depth 2 (reachable + visible): 2234 grids;
depth 3 (reachable + visible): 835 grids;
depth 4 (reachable + visible): 298 grids;
depth 5 (reachable + visible): 139 grids;
depth 6 (reachable + visible): 679 grids;
depth 7 (reachable + visible): 1438 grids;
depth 8 (reachable + visible): 611 grids;
depth 9 (reachable + visible): 76 grids;
depth 10 (reachable+visible): 194 grids;
depth 11 (reachable+visible): 349 grids;
depth 12 (reachable+visible): 96 grids;
Depth 13 (reachable+visible): 51 grids;
average topological depth= 37246 (total depth)/8080 (total grid number) = 4.610.
Each time a topological search of the visual relationship is established on the previous newly added reachable spatial position until all grids are exhausted. This results in an average topological depth of the other grid "seen" from the point J.
Referring to fig. 7, fig. 7 is a specific implementation step of step S123 of the view relationship analysis method of the present application, where calculating, based on the reachable grid matrix and the visible grid matrix, an average depth of view of each grid by using a second preset method includes:
step S1231: the first number of grids is taken as targets, grids of the direct visual starting point grids are obtained and marked as visual grid areas, and the number of grids of the visual grid areas is D 0
Step S1232: and removing grids of the visible grid area from the first number of grids to obtain the rest grids.
Step S1233: executing a first reachable topology in the remaining grids, obtaining the number of grids in the remaining grids, which can reach the visible grid area, and recording as the newly increased reachable grid number D of the first reachable topology 1
Step S1234: and adding the newly added reachable grid obtained by the last reachable topology into the visible grid area to generate a new visible grid area.
Step S1235: and eliminating the new visible grid area from the residual grids to obtain new residual grids.
Step S1236: executing the ith reachable topology in the new remaining grids to obtain the number of grids in the new remaining grids, which can reach the new visible grid area, and recording as the newly increased number of reachable grids D of the ith reachable topology i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i is a positive integer.
Step S1237: and repeatedly executing the operation until the new residual grid quantity is reduced to zero, and stopping the topology operation.
Step S1238: grid number D based on the visual grid area 0 Current reachable topology depth i, newly added reachable grid number D of the ith reachable topology i And carrying out the total times of the reachable topology and the total grid number, and calculating the average observed depth of the starting point grid.
Figure BDA0003010154050000131
Figure BDA0003010154050000141
The calculation thought of the codes is as follows:
finding out grids which can directly see the starting point grids from the graph, marking the grids as current visible grid areas, finding out the number of grids which can reach the current visible grid areas through one-time reachable topology from the remaining grids each time, adding the searched reachable grids into the visible grid areas, and removing the reachable grids from the remaining grids; the search for grids that arrive through the one-time reachable topology continues from the remaining grids until all grids in the map are searched.
Let the current reachable topology depth be i, and the number of reachable grids of the ith reachable topology be D i The total number of times of topology is reached is n, and the number of grids in the map, which can directly see the starting point grids, is D 0 If the total grid number is C, the calculation formula of the average depth of view is:
Figure BDA0003010154050000142
the specific steps of the algorithm code are as follows:
1) Finding out grids from the map, which can directly see the starting point grids, and recording the number of corresponding grids as D 0
2) Finding a grid from the map, wherein the grid can directly see the starting point grid, and recording the starting point grid as a current visible grid area;
3) Searching the number of grids which are accessible by one-time topology in the residual grids with the visible grids removed, and recording the number of newly-increased accessible grids which are accessible by the first-time topology as D 1
4) Will D 1 Adds to the visible grid area and eliminates the last reachable grid D in the rest grids 1 Searching the number of the grids which are reachable through one time in the rest grids, and recording the number of the reachable grids as the second time topology as D 2
5) Will D 2 To the area of the visual grid,and eliminating the last reachable grid D from the rest grids 2 Searching the number of the grids which are reachable through one time in the rest grids, and recording the number of the reachable grids as the second time topology as D 3
6) And so on until the number of the remaining grids is reduced to zero, and the topology stops;
7) According to equation 2, the average perceived topological depth of the starting point grid is calculated.
In the above embodiment, the following beneficial effects exist: ensuring the correct computation of the average perceived depth of each grid, thereby better quantifying the "seen" spatial experience.
In one embodiment, the average perceived depth of each grid is the average topological depth of any grid reachable or visible starting grid in the spatial syntactic analysis base.
Specifically, referring to the right graph of fig. 6, a schematic diagram of a measurement method of the average perceived topological depth of the point J is shown, as the right graph of fig. 6, the average topological depth of the point J is "seen".
Depth 1 (visible): 1080 grids;
depth 2 (reachable): 1598 grids;
depth 3 (reachable): 879 grids;
depth 4 (reachable): 1930 grids;
depth 5 (reachable): 1243 grids;
depth 6 (reachable): 929 grids;
depth 7 (reachable): 326 grids;
depth 8 (reachable): 95 grids;
average topological depth= 29464 (total depth)/8080 (total grid number) = 3.647.
As can be seen from the right-hand graph of fig. 6, for the "seen" index calculation, there are and only the connections of the first topological depth are visual relationship connections, and all other topological depths are reachable relationship connections.
Referring to fig. 8, fig. 8 is a second embodiment of the view relationship analysis method of the present application, where the method further includes:
step S210: and obtaining the reachable relation data and the visible relation data of each grid in the building plan by a preset method.
Step S220: and calculating the average visible depth and the average observed depth of each grid according to the reachable relation data and the visible relation data based on the reachable space of the building plan, and completing the view relation analysis of each grid.
Step S230: based on the analysis result of the view relationship of each grid, a visualization operation is performed.
The second embodiment includes step S230 compared with the first embodiment, and other steps have been described in the first embodiment, which is not described herein.
Specifically, the txt file of the calculation result may be imported into a VGA analysis file of the depthmap x and visualized, and specific implementation steps are described in chapter 4.5.3 of the chapter 4 of the space syntax course, and are not described herein. The average depth of the reachable layers of the network teacher garden space, the average depth of the visible layers, and the comparison of the average depth of "seen" and "seen" are shown in fig. 9; as shown in fig. 9, for comparison of new and old methods of visual analysis (VGA), the two left pictures are average depths of the reachable layer and the visual layer of the network teacher garden analyzed by the VGA method of the space syntax prior art; the two pictures on the right are the space depth analysis of 'seen' and 'seen' in the embodiment; it should be noted that the darker the grid color in fig. 9, the smaller the average topology depth is represented.
In the above embodiment, the following beneficial effects exist: after the visualization operation is performed, the method can be easily seen to better reveal the space perception characteristics of different parts of gardens.
The present application also provides a computer storage medium, on which a program of a visual field relation analysis method is stored, which when executed by a processor implements the steps of any one of the above visual field relation analysis methods.
The application also provides a visual relationship analysis device, which comprises a memory, a processor and a program of a visual relationship analysis method stored in the memory and capable of running on the processor, wherein the processor realizes the steps of any one of the visual relationship analysis methods when executing the program of the visual relationship analysis method.
The present application relates to a visual field relationship analysis apparatus 010 including as shown in fig. 10: at least one processor 012, a memory 011.
The processor 012 may be an integrated circuit chip having signal processing capability. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software form in the processor 012. The processor 012 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 011, and the processor 012 reads information in the memory 011 and performs the steps of the above method in combination with its hardware.
It is to be appreciated that memory 011 in embodiments of the present invention can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (Double data rate SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and Direct memory bus RAM (DRRAM). The memory 011 of the systems and methods described by embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims (6)

1. A method of view relationship analysis, the method comprising:
obtaining a building plan;
drawing the building plan into a space syntactic analysis base map, and dividing the space syntactic analysis base map into a first number of grids with equal size;
based on the space syntactic analysis base map, storing the reachable attribute data of each grid into a first data table in turn according to the serial number sequence of the grids, and generating a reachable layer space relation graphic data table;
based on the space syntax analysis base map, sequentially storing the visual attribute data of each grid into a second data table according to the serial number sequence of the grids, and generating a visual layer space relation graphic data table;
Acquiring an reachable grid matrix and a visible grid matrix of each grid through the serial number of the grid based on the reachable layer space relation graphic data table and the visible layer space relation graphic data table;
calculating the average visible depth of each grid by using a first preset method based on the reachable grid matrix and the visible grid matrix;
calculating the average perceived depth of each grid by using a second preset method based on the reachable grid matrix and the visible grid matrix;
completing analysis of the view relationship of each grid;
the method for calculating the average visual depth of each grid by using a first preset method based on the reachable grid matrix and the visual grid matrix comprises the following steps:
s1221: selecting a starting point grid, wherein the number of visible grids corresponding to the starting point grid isV 0 The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the starting point grid is any grid in the space syntactic analysis base graph;
s1222: starting from the starting point grid, executing a first reachable topology, obtaining the total number of the directly reachable grids of the first reachable topology and the directly reachable grids corresponding to the directly reachable grids, and recording the total number as the newly added number of the directly reachable grids of the first reachable topology V 1
S1223: starting from any newly added visual grid of the last reachable topology, executing the firstiA secondary reachable topology, obtaining the firstiThe total number of directly reachable grids of the secondary reachable topology and the directly reachable grids corresponding to the directly reachable grids is recorded as the firstiNew incremental visual grid number for sub-reachable topologyV i; wherein ,iis a positive integer;
s1224: repeating steps S1221 to S1223 until the number of visible grids of the starting grid reaches the total number of grids minus 1, and stopping the topology operation; wherein the total grid number is the first number;
s1225: based on the number of visible grids corresponding to the starting gridV 0 Current reachable topology depthiSaid first stepiNew incremental visual grid number for sub-reachable topologyV i The total times of the reachable topology and the total grid quantity are carried out, and the average visible depth of the starting point grids is calculated;
the calculating the average depth of view of each grid by using a second preset method based on the reachable grid matrix and the visible grid matrix comprises the following steps:
s1231: the first number of grids is used as targets, grids of the direct visual starting point grids are obtained and marked as visual grid areas, and the number of grids of the visual grid areas is D 0
S1232: removing grids of the visible grid area from the first number of grids to obtain remaining grids;
s1233: executing a first reachable topology in the remaining grids, obtaining the number of grids in the remaining grids, which can reach the visible grid area, and recording the number of grids as a new reachable grid number of the first reachable topologyD 1
S1234: adding the newly added reachable grid obtained by the last reachable topology into the visible grid area to generate a new visible grid area;
s1235: removing the new visible grid area from the remaining grids to obtain new remaining grids;
s1236: executing the first in the new remaining gridiA sub-reachable topology, obtaining the number of grids in the new remaining grids, which can reach the new visible grid area, which is recorded as the firstiNewly added number of reachable grids of sub-reachable topologyD i; wherein ,iis a positive integer;
s1237: repeating steps S1231 to S1236 until the new remaining number of grids is reduced to zero, and stopping the topology operation;
s1238: grid number based on the visual grid areaD 0 Current reachable topology depthiSaid first stepiNewly added number of reachable grids of sub-reachable topology D i And carrying out the total times of the reachable topology and the total grid number, and calculating the average observed depth of the starting point grid.
2. The visual field relation analysis method of claim 1, wherein the average visual depth of each grid is an average topological depth at which any one starting grid in the space syntax analysis base map is reachable or at which other grids are visible.
3. The visual field relation analysis method of claim 1, wherein the average perceived depth of each grid is the average topological depth of any one of the grid reachable or visible starting point grids in the spatial syntactic analysis base.
4. The visual field relationship analysis method of claim 1, wherein the method further comprises:
based on the analysis result of the view relationship of each grid, a visualization operation is performed.
5. A computer storage medium, wherein a program of a visual field relation analysis method is stored on the computer storage medium, and the program of the visual field relation analysis method realizes the steps of the visual field relation analysis method according to any one of claims 1 to 4 when being executed by a processor.
6. A visual field relation analysis device comprising a memory, a processor and a program of visual field relation analysis methods stored on the memory and executable on the processor, the processor implementing the steps of the visual field relation analysis method of any one of claims 1 to 4 when executing the program of visual field relation analysis method.
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Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231130

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Application publication date: 20210625

Assignee: Shenzhen Jinchengyu Decoration Engineering Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980050232

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231205

Application publication date: 20210625

Assignee: Shenzhen Weitai Building Materials Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980049901

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231204

Application publication date: 20210625

Assignee: Shenzhen Yajun Decoration Design Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980049899

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231204

Application publication date: 20210625

Assignee: Shenzhen Yijia Construction Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980049897

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231204

Application publication date: 20210625

Assignee: Shenzhen Yongji Construction Engineering Inspection Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980049891

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231204

Application publication date: 20210625

Assignee: Zhenfeng Decoration Design Engineering (Shenzhen) Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980049887

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231204

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Assignee: Shenzhen everything Safety Technology Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980050514

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231207

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Application publication date: 20210625

Assignee: Shenzhen Yangxin Decoration Engineering Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980052132

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231213

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Application publication date: 20210625

Assignee: AVIC intelligent construction (Shenzhen) Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2023980054566

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20231228

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Assignee: SHENZHEN GENERAL BARCODE'S TECHNOLOGY DEVELOPMENT CENTER

Assignor: SHENZHEN University

Contract record no.: X2024980000040

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20240103

Application publication date: 20210625

Assignee: Shenzhen Subangbo Intelligent Technology Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2024980000038

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20240103

Application publication date: 20210625

Assignee: Shenzhen Deep Sea Blue Ocean Technology Service Center

Assignor: SHENZHEN University

Contract record no.: X2024980000036

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20240104

EE01 Entry into force of recordation of patent licensing contract
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Application publication date: 20210625

Assignee: Luoding Zhongda Technology Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2024980000187

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20240105

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Application publication date: 20210625

Assignee: SHENZHEN HONGHUI INDUSTRIAL Co.,Ltd.

Assignor: SHENZHEN University

Contract record no.: X2024980000463

Denomination of invention: Analysis methods, devices, and computer storage media for field of view relationships

Granted publication date: 20230428

License type: Common License

Record date: 20240110