JPH03201068A - Designing device - Google Patents

Abstract

PURPOSE:To specify and output a part of a design picture to be corrected by comparing an evaluating word which is inferred from the design picture with an input expected evaluating word. CONSTITUTION:An evaluating word 9 set previously is stored in a memory M of a computer together with the knowledge 11 which prescribes the relation between the words 9, the car design elements 13, the knowledge 15 which prescribes the relation between the words 9 and the elements 11, etc. Then the categories are decided for each item of a design picture with operation of a keyboard 3. Thus the word 9 is inferred by the function of a CPU 7, and an expected evaluating word of the design picture is inputted with operation of the keyboard 3. Then both evaluating words are compared with each other. Based on the result of comparison, a part to be corrected is specified in the design picture in order to secure the coincidence between both evaluating words. Then the specified part of the design picture is displayed on a CRT 5 together with the design picture itself. Thus it is possible to specify the part to be corrected if the desired impression is not coincident with the input design picture.

Description

[Detailed Description of the Invention] [Objective of the Invention] (Industrial Application Field) The present invention is a design for displaying the design of a vehicle on an output means such as a CRT while confirming the image people have of the vehicle. Regarding equipment.

(Prior art) This type of design device includes, for example, "iVo, Journal of the Institute of Electronics, Information and Communication Engineers, published by the Institute of Electronics, Information and Communication Engineers, March 1988.
71 No. 3 PP245-257" as shown in FIG. 11. This is a computer memory that records the exterior appearance of a house for each part of the house, such as the entrance, Western-style room, Japanese-style room, kitchen, bath, etc., as well as evaluation terms such as ``luxury,''``spacious,'' and ``spacious'' as adjectives that express the feeling. , knowledge that defines the relationships between evaluation terms;
The knowledge that defines the relationship between these evaluation terms and housing design elements is stored as a knowledge database, and a human being operates an evaluation terminology input means such as a keyboard to create a Japanese-style room that represents design elements that are constituent parts of a house, for example. When you enter a limited term for housing design and an evaluation term such as ``spacious'' that expresses your image of a Japanese-style room into the computer, the computer uses the input terminology from the knowledge database to determine the appropriate evaluation term. It is configured to infer and extract the design elements of a Japanese-style room and display the images on the display means.

(Problems to be Solved by the Invention) By the way, in such a design device, if technical evaluation terms are made to correspond to vehicle design, it can be put to practical use as a vehicle design device. However, the input as evaluation terms was done in object words, and the output was, for example, the design of a vehicle interior, so when designers actually use this device, they can get design hints, but they cannot draw it themselves. The problem was that it was completely unclear whether the design drawings would give the desired impression, and what parts should be modified to achieve that.

SUMMARY OF THE INVENTION An object of the present invention is to provide a design device that can specify parts of a design drawing that should be corrected when the input design drawing differs from the intended impression.

[Structure of the invention] (Means for solving the problem) In order to solve the above problem, this invention has the following features as shown in FIG.
A first input means CL1 for inputting a design drawing, a second input means CL2 for inputting an expected image of the inputted design drawing, and a comparison means CL3 for comparing the image of the inputted design drawing with the expected image. Based on this comparison, the design drawing is configured to include a discriminating means CL4 that identifies a portion of the design drawing that should be corrected in order to make the image substantially match the expected image, and an output means CL5 that outputs the result of this discriminating means CL5. .

(Operation) According to the above configuration, when a design drawing is inputted by the first input means CLI and an expected image of the inputted design drawing is inputted by the second input means CL2, the image of the inputted design drawing and the expected image are Comparison means CL3 compares the design drawings, and based on this comparison, determination means CL4 identifies parts of the design drawings that should be modified in order to make the image of the design drawings substantially match the expected image. The result of this determination means CL4 is outputted by output means CL5.

(Example) The present invention will be described in detail below.

FIG. 2 shows a schematic configuration diagram of one embodiment, and this design apparatus is composed of a computer 1, a keyboard 3, and a CRT 5.

The computer 1 includes a memory M as a knowledge database and a CPU 7 as a calculation means CL2.

Here, the memory M stores evaluation terms 9, knowledge 1A11 that defines relationships between evaluation terms, vehicle design elements 13, and knowledge 15 that defines relationships between evaluation terms and design elements.

The evaluation terms 9 are composed of adjective words as shown in the evaluation words in Table 1 of FIG.

Knowledge 11 that defines the relationship between evaluation terms is knowledge that was obtained by collecting evaluation terms 9 as shown in Table 1 and analyzing the results of a preliminary experiment to define the relationship between evaluation terms. This relationship means, for example, that evaluation term 9 is defined by quantification theory I.
Data is obtained by dividing factors into factors 1 to 10 based on human senses through multivariate analysis such as ``class'' or ``class'', and the degree of relationship between each evaluation term and each factor is obtained as a factor loading (numerical value). It can be said that terms with close numerical loadings on each factor are closely related and similar. Knowledge 11 that defines the relationship between evaluation terms selects the most similar term when the input evaluation term is not in the evaluation term group used in the sensory evaluation experiment described later when using the design device. It is also used to create a factor axis, which will be described later.

The vehicle design element group 13 is divided into categories for each item, such as the number of meters in the vehicle interior, as shown in Table 2 of FIG.

Knowledge that defines the relationship between evaluation terms and vehicle design elements 1
No. 5 was obtained as a result of the sensory evaluation experiment as shown in Table 2 above. Specifically, we select evaluation terms and vehicle design elements 11, show the vehicle design elements corresponding to each item to an unspecified number of people, and evaluate the vehicle for each evaluation term 9, which is a group of adjective words. Feelings received from design elements are collected, and the accumulated results are analyzed as partial regression coefficients (correlation coefficients) using multivariate analysis such as quantification theory type I or type II.

Here, as shown in Table 2, the items include the number of meters provided on the instrument panel in vehicle design element group 13, the instrument panel and meter cluster, the meter cluster and center console, the thickness of the door, the overhang of the center cluster, Each of these focuses on armrests, etc.

The number of meters is classified into five categories. Namely, the first category has one large meter, the second category has one large meter and two small meters, the third category has one large meter and three small meters, and the third category has two large meters. and one small meter, and a fifth category has two large meters and two small meters.

Items focused on instrument panels and meter clusters are divided into two categories. That is, there are a first category in which the instrument panel and meter cluster are integrated, and a second category in which the instrument panel and meter cluster are separated.

The third item, which focuses on the meter cluster and center console, is divided into two categories. In other words, the first model that combines the meter cluster and center console.
category, and a second category in which the meter cluster and center console are separated.

The fourth item, which focuses on the thickness of the door, is divided into two categories. That is, the first category has thick doors, and the second category has thin doors.

Items that focus on the overhang of the center cluster are classified into two categories. That is, the first category has a center cluster overhang, and the second category has no center cluster overhang.

The sixth item focusing on armrests and other items are classified into categories below.

The keyboard 3 constitutes a first input means CL1 for design drawings, and is used to determine a category for each item by operating the keyboard and create a design drawing. The keyboard 3 also constitutes a second input means CL2 for inputting expected evaluation terms of the input design drawing.

The CPU 7 infers an evaluation term from the knowledge database based on the input design drawing, and also includes a comparing means CL3 that compares the inferred evaluation term with the input expected evaluation term, and further infers an inferred evaluation term based on this comparison. In other words, in order to make the image of the design drawing approximately match the image of the expected evaluation term, it constitutes a determining means CL4 that specifies a portion of the design drawing that should be corrected.

The CRT 5 constitutes an output means CL5 for outputting the determination results, and displays the design drawing as an image.

Evaluation terms 9 preset with the above configuration, knowledge 11 that defines relationships between evaluation terms, vehicle design elements 13, and knowledge 15 that defines relationships between evaluation terms and vehicle design elements.
etc. are allocated in the memory M of the computer. In this state, when a category for each item is determined by operating the keyboard 3, the CPU 7 extracts design elements from the knowledge database and displays them as a design diagram on the CRT5.
to be displayed. Further, an evaluation term is inferred from the knowledge database based on the input design drawing, and when the expected evaluation term of the design drawing inputted by operating the keyboard 3 is input, the inferred evaluation term and the input expected evaluation term are are compared.

Based on this comparison, a portion of the design drawing that should be modified in order to make the inferred evaluation term match the expected evaluation term is specified, and the result is displayed on the CRT 5 together with the design drawing.

The process will be explained below based on the flowchart shown in FIG.

First, in step S1, the design designed by the designer is
- A diagram is input by operating the keyboard 3, and in the next step S2, the category of each item is read from the input design diagram. In step S3, the expected evaluation term for the design drawing input by the designer is input by operating the keyboard 3.

Then, in step S4, it is determined whether the evaluation term inferred from the design drawing and the input expected evaluation term are the same, and if they are the same, a message such as "The picture is as expected" is displayed in step S5. It is displayed on the CRT5 together with the input design drawing. Therefore, the designer can immediately know whether the design drawing he has designed is exactly as he imagined.

If it is determined in step S4 that the evaluation term inferred from the design drawing is different from the input expected evaluation term, the combination of categories inferred from the input expected evaluation term is read in step S6. For example, if the adjective ``Kino inside the raceway'' is input as an expected evaluation term, this reading is performed by calculating the partial regression coefficient of the category extracted for each item among the partial regression coefficients corresponding to this evaluation term. The top n category patterns are read starting from the one with the largest sum.

In step S7, the category pattern of one input design drawing is compared with the category pattern group inferred in step S6, and in step S8, the inferred category pattern most similar to the category pattern of the input design drawing is selected. It will be done.

The inferred category pattern thus selected and the category pattern of the inputted design drawing are compared in step S9, and portions of the category of the design drawing that are different from the categories of the inferred category pattern are identified and displayed on the CRT 5. This is displayed blinking among the input design drawings (step 510). Therefore, the designer can immediately know which parts of the design drawing that he or she has imagined are different and not as intended, and can easily grasp the parts that need to be corrected.

FIG. 6 shows a subroutine for inputting a design drawing in step S1. First, in step s21, one item from among a plurality of items, for example, the number of meters, is input by operating the keyboard 3. By this operation, a graphic screen as shown in FIG. 7(a) is displayed on the CRT 5. The designer inputs a category by operating the keyboard 3 while looking at the displayed screen. here,
For example, assume that a fourth category with a large meter 2Mi and one small meter is input (step 523). Once the category for the input item is input in this way, it is stored in the memory M (step 524). Then, in step S25, it is determined whether or not category input has been completed for all items, and the steps 521 to S24 described above are performed for all items.

The category for the item thus input is, for example, No. 8V! Each category is circled in Table 3 of J. Note that Table 3 is the same as Table 2 in FIG. In other words, the number of meters is 2. 1st grade. We input information such as whether the instrument cluster and meter cluster are one piece, the meter cluster and center console are one piece, the door thickness is thick, and the center cluster has an overhang. Such input is performed based on the designer's image, and the design drawing thus input is displayed on the CRT as the final screen shown in Figure 7(b).
This is what is displayed in 5.

The evaluation reasoning in step S3 will be further explained using Table 3. Table 3 is the same as Table 2 of partial regression coefficients showing the correspondence between item categories and evaluation terms, as described above. Completion of the design drawing as described above means that each category is determined for each item as explained above in Table 3. The total column on the right side shows the partial regression coefficient of the selected category added horizontally for each evaluation term. It can be said that the higher this number is, the more representative the impression that the general public gets from the design drawing. For example, in Table 3, it can be said that the impression of ``J'' in ``Running Indoor A'' is the strongest.The second place is ``Bright''.
It can be said that this gives a strong impression.

FIG. 9 is a correspondence table in which the category pattern of the input design drawing in step S7 in FIG. 5 is compared with the inferred category pattern group.

In FIG. 9, the circled areas indicate the corresponding categories. In this example, seven patterns are selected as inferred categories, and the number of matches between the category pattern of the input design drawing and the category is shown at the right end of the table for each inferred category pattern. Therefore, in step S8 of FIG. 5, the inferred category pattern 5 with the largest number of matching categories is selected.

The image output as a result of the comparison in step SIO is, for example, as shown in FIG. As shown in FIG. 10, the part of the input category that is different from the inferred category is identified by a blinking display. Furthermore, as shown in FIG. 10, a verbal display can also be displayed at the same time to indicate which category should be changed and how.

Next, if there are a plurality of correction points to be supported as shown in FIG. 10, for example, the corrections can be prioritized. In other words, among the categories of the design drawings input as shown in Figure 8, Table 3, the thickness of the door can be changed from "thick" to "thin".
, change the center cluster overhang from “with” to “without”
For example, in the former modification, the partial regression coefficient determined by the expected evaluation term changes from 0.11 to 0.
9, and the latter correction goes from 0.19 to -0.06, and the difference is 0.2 in the former and 0.25 in the latter.
It is. In this way, the larger the difference between the partial regression coefficients before and after correction, the more different it is from the designer's image, so in the above case, the center cluster overhang can be changed from "with" to "no". Priority shall be given to cases where modifications are made to

In the above embodiment, the design drawings are input by determining the item and category using the keyboard, but it is also possible to input the design drawings written on paper by reading them with an image scanner. Differences in preference due to engine displacement, age, etc. may be input into the expected evaluation terms to be input. In the above example, when comparing the category pattern of the design drawing and the inferred category pattern, multiple inferred category patterns are extracted from the expected evaluation terms, and furthermore, from these multiple inferred category patterns, the category pattern closest to the inputted design drawing category pattern is extracted. Comparisons were made by extracting things, but from the input expected evaluation terms, only one category pattern that is closest to the expected evaluation term was extracted, and this category pattern was compared with the category pattern of the input design drawing. You may also make a comparison. In the above embodiment, the evaluation term inferred from the design drawing and the input expected evaluation term are first compared to see if they are the same, but the input design drawing and the design drawing inferred from the expected evaluation term are directly compared. It can also be configured to compare and determine whether the image is as desired. Furthermore, in the above embodiment, the designer
Although it was used to obtain the P price, it can also be used by ordinary users when deciding on a desired interior design, etc. while confirming their own image at a dealer or the like. Furthermore, this design device can be applied not only to the interior of the vehicle but also to the exterior and other designs, and can also be applied to architectural design and other areas.

[Effect of the invention j As is clear from the above, according to the configuration of the present invention, by comparing the image of the input design drawing and the expected image, the image of the design drawing is corrected to almost match the expected evaluation image. It is possible to specify and output the parts of the design drawing that should be output. Therefore, a designer or the like can design while checking whether or not the design drawing he or she has designed matches the image he or she has in the design drawing.

[Brief explanation of drawings]

Fig. 1 is a block diagram of the present invention, Fig. 2 is a schematic block diagram of one embodiment, and Fig. 3 is a table 1 of knowledge that defines the relationship between evaluation terms.
, *Figure 4 is Table 2 of knowledge that defines the relationship between evaluation terms and each item of vehicle design elements, Figures 5 and 6 are flowcharts, Figure 7 is a CRT output screen diagram, and Figure 8 is evaluation Table 3 of knowledge that defines the relationship between terms and each item of vehicle design elements, and Figure 9 is Table 4 of category pattern selection.
, FIG. 10 is an output screen diagram of a CRT, and FIG. 11 is a block diagram of a conventional example. CLI...First input means Cl3...Second input means Cl3...Comparison means Cl4...Discrimination means Cl5...Output means

Claims (1)

[Claims] a first input means for inputting a design drawing; a second input means for inputting an expected image of the inputted design drawing; a comparison means for comparing the image of the inputted design drawing with the expected image; A design device comprising: a determining means for specifying a portion of a design drawing that should be corrected in order to make the image of the design drawing substantially match an expected image based on the image; and an output means for outputting the result of the determining means.