JP2023098551A - Lip evaluation method - Google Patents

Abstract

To provide a technique for evaluating characteristics of a lip or body of a subject using a plurality of factors including one or more factors belonging to a physiological information category of the subject as input factors and using factors different from the input factors as output factors.SOLUTION: A lip evaluation method evaluates characteristics of a subject's lip or body using a plurality of factors including one or more factors belonging to a physiological information category and using factors different from the input factors as output factors, out of a category group consisting of the physiological information category using physiological characteristics relating to the subject's lip or body as factors, a sensitivity information category using sensory characteristics relating to the subject's lip or body as factors, and a color information category using color information relating to the subject's lip or body. The output factors are calculated based on a mathematical model acquired in advance from the population and representing a correlation between the plurality of input factors and output factors and the plurality of input factors acquired from the subject.SELECTED DRAWING: Figure 10

Description

The present invention relates to a lip evaluation method.

There is a method of determining a user's lip color and selecting a lipstick with a color that matches the user's lip color category based on the lip color category using a lipstick selection chart (Patent Document 1).

JP-A-2008-62042

In Patent Document 1, a user's lip color is classified into lip color categories based on lightness, saturation, and hue using a lip color scale. However, as research progresses, there is a possibility that classification based on color-related information such as brightness, saturation, and hue may not be sufficient, and there is room for improvement.

The present invention has been made in view of the above problems, and relates to a lip evaluation method for evaluating the lip using information belonging to the physiological information category in which the physiological characteristics of the lip of a subject or the age of the subject are factors.

The present invention includes a physiological information category whose factors are physiological characteristics of the lips or body of a subject, a sensory information category whose factors are sensory characteristics of the lips or body of the subject, and a color of the lips or body of the subject. From a category group consisting of color information categories with information as a factor, a plurality of factors including one or more of the factors belonging to the physiological information category are used as input factors, and the factors different from the input factors are used as output factors. a mathematical model obtained in advance from a population and showing the correlation between the plurality of input factors and the output factors; and a plurality of the input factors obtained from the subject. and a lip evaluation method characterized by determining the output factor based on.

In addition, the present invention includes a physiological information category whose factors are physiological characteristics related to the lips or body of a subject, a sensory information category whose factors are sensory characteristics related to the lips or body of the subject, and the lips or body of the subject. A plurality of factors including one or more of the factors belonging to the physiological information category are used as input factors from a category group consisting of color information categories whose factors are color information related to color information, and the factors different from the input factors are used as output factors. A system for evaluating the lip or body characteristics of the subject, comprising storage means for storing a mathematical model obtained in advance from a population and showing the correlation between the plurality of input factors and the output factor; The present invention relates to a lip evaluation system comprising input means for inputting a plurality of acquired input factors, and calculation means for obtaining the output factors based on the mathematical model and the input factors.

According to the method provided by the present invention, it is possible to evaluate the lips using information belonging to the physiological information category, so that the lips can be evaluated using multifaceted information.

(a) The lip color is a diagram showing the chromatic characteristics of the pink type, (b) The lip color is a diagram showing the chromatic characteristics of the pale type, (c) The lip color is purple. (d) The chromatic characteristics of brown type lip color. (a) is a diagram showing the distribution of L ^* (brightness) of the lip for each color type of the lip, (b) is a diagram showing the distribution of C ^* (chroma) of the lip for each color type of the lip, and (c) FIG. 10 is a diagram showing the distribution of h (hue) of the lips for each color type of the lips; FIG. 10 is a diagram showing the ratio of test subjects by lip color type by age group. It is a figure which shows the relationship between a lip color type and a melanin index. It is a figure which shows about the color type and ATI (blood flow peak position) of a lip. FIG. 4 is a diagram showing an example of an MBR time waveform; It is a figure which shows each part of a lip. FIG. 4 is a diagram showing the correlation between lip color and body visual category. It is a flow chart which shows a lip evaluation method. FIG. 10 is a diagram showing an outline of an implementation pattern 1; FIG. 10 is a diagram showing an outline of an implementation pattern 2; FIG. 11 is a diagram showing an outline of implementation pattern 3; FIG. 11 is a diagram showing an outline of an implementation pattern 4; FIG. 11 is a diagram showing an outline of an implementation pattern 5; FIG. 11 is a diagram showing an outline of an implementation pattern 6; 1 is a conceptual diagram of a lip information evaluation system; FIG.

Preferred embodiments of the present invention are described below with reference to the drawings. The drawings of the present embodiment are all for explaining the technical idea, configuration and operation of the present invention, and do not specifically limit the configuration. Moreover, in all the drawings, the same constituent elements are denoted by the same reference numerals, and overlapping descriptions are omitted as appropriate.

<Overview>
An overview of the lip evaluation method according to the present embodiment will be described.
The lip evaluation method of the present embodiment (hereinafter sometimes referred to as this method) includes physiological information categories that are factors of physiological characteristics related to the lips or body of the subject, sensory characteristics related to the lips or body of the subject A plurality of factors including one or more factors belonging to the physiological information category are input from a category group consisting of a sensory information category with factors and color information categories with color information related to the lips or body of the subject as factors. A method of evaluating the characteristics of the lips or body of the subject using the factor as a factor and the factor different from the input factor as an output factor, wherein the correlation between the plurality of input factors obtained in advance from a population and the output factor The output factor is determined based on a mathematical model representing the relationship and the plurality of input factors acquired from the subject.

Hitherto, classification of lip colors has been performed only by differences in lip color information such as brightness, saturation, and hue, as in Patent Document 1, for example. However, the difference in lip color is affected by the physiological characteristics of the lip, such as the type and amount of pigment contained in the lip, differences in lip blood flow characteristics, lip shape, and physiological information such as the subject's age. there is The present inventors have come to the knowledge that it is important to consider physiological information in addition to lip color information such as brightness, saturation, and hue. Therefore, we propose a lip evaluation method that evaluates the lip using information belonging to the physiological information category in which the physiological characteristics of the subject's lip or body are factors.

This lip evaluation method uses a plurality of factors including one or more factors belonging to the physiological information category among a large number of factors belonging to the physiological information category, a large number of factors belonging to the emotional information category, and a large number of factors belonging to the color information category. Perform lip evaluation using In order to facilitate understanding of the present invention, of the color group factors classified using lip pigment information, the color group A factors (factors belonging to the color type category) and the factors belonging to the color information category (L ^* (brightness ), C ^* (saturation), and h (hue)), and then each factor and each category will be described.

FIG. 1 shows the results of determining the lip color (mainly the lower lip) of 85 Japanese women in their 20s to 70s and classifying the lip color. The evaluation was visually performed by three professional evaluators who are familiar with the lip color. First, judgment is made so that the number of types of similar lip colors is as small as possible (first time), and after a predetermined number of days, judgment is made again using the same photo (second time), and as the final color classification Decided. In addition, when the results differed between the first and second judgments, a re-judgment was performed. As a result of the determination, as shown in FIG. 1, the lip color of Japanese women can be classified into four types. In this specification, provisional color names are given to each of them, and they are referred to as (a) pink type, (b) pale type, (c) purple type, and (d) brown type. However, there is no clear boundary, and in many cases there are multiple types, such as a pink type and a pale type. Here, the absence of a clear boundary means that the four groups of color information (L ^* , C ^* , h, etc.) have different center values, but are not separated completely without overlapping, and are partially overlapping regions. means that there exists
Here, the characteristics of each type will be described.

The pink type in FIG. 1(a) is a bright red lip color. Also, L ^* is high, C ^* is high, and h is low.
FIG. 1(b) Pale type is a lip color without redness. Also, L ^* is high, C ^* is low, and h is high.
FIG. 1(c) purple type is a lip color with low saturation. Also, L ^* is high, C ^* is low, and h (hue) is low.
FIG. 1(d) Brown type is a dark lip color. Also, L ^* is low, C ^* is low, and h is high.

FIGS. 2(a) to 2(c) show what color types are distributed to what values of L ^* , C ^* , and h, respectively, based on the determination results of FIG.
FIG. 2(a) is a diagram showing the distribution of L ^* of the lip of the subject by color type. The horizontal axis indicates the color type, and the vertical axis indicates the value of L ^* . As is clear from FIG. 2(a), the pink type, pale type, and purple type do not have a large difference in the distribution of L ^* values, but the brown type has many distributions with low L ^* values. There is no significant difference between the pink type, the pale type and the purple type, but there is a significant difference between the purple type and the brown type, and there is a significant difference between the pink type and the brown type, and between the pale type and the brown type. There is a difference.
FIG. 2(b) is a diagram showing the C ^* distribution of the subject's lips by color type. The horizontal axis indicates the color type, and the vertical axis indicates the saturation value. As is clear from FIG. 2(b), the pink type is distributed at high C ^* values, while the pale type, purple type, and brown type are distributed at low C ^* values. . There is a significant difference between the pink type and each other type, and there is also a significant difference between the pale type and the purple type, and between the purple type and the brown type.
FIG. 2(c) is a diagram showing the distribution of h of the subject's lips for each color type. The horizontal axis indicates the color type, and the vertical axis indicates h. The redder the lip color, the lower the value of h. As is clear from FIG. 2(c), the pink type and purple type have relatively low h values, while the pale type and brown type have high h values. There is a significant difference between the pink type and the pale type, and between the pink type and the brown type.

FIG. 3 is a diagram showing which color type subjects are distributed according to age. The horizontal axis indicates age, and the vertical axis indicates the percentage of subjects with the included color types. For example, people in their 20s have a high percentage of pink types, and people in their 70s have a high percentage of purple types. In addition, as the age increases, the ratio of the pink type decreases. In this way, the ratio of subjects with the included color types differs depending on the age group.

FIG. 4 is a diagram showing the distribution of the melanin index (MI) of the lips of subjects according to color type. The horizontal axis indicates the color type, and the vertical axis indicates the MI. Among the four types, the pink type, pale type, and purple type are distributed at low MI values, and the brown type is distributed at high MI values. There is a significant difference among the brown type, pink type, pale type, and purple type.

FIG. 5 is a diagram showing ATI (blood flow peak position) for each color type. A lower ATI indicates a faster time to peak. Blood flow peaks early in the pink type, and late in the pale and purple types.
Table 1 shows the summarized contents of FIGS.

As shown in Table 1, the factors (L ^* , C ^* , h) belonging to the color information category, the factors (MI, ATI) belonging to the physiological information category, and the features estimated therefrom are used to type the lip color. By categorizing into , when proposing makeup methods, makeup products, care methods, care products, etc. based on the classification results, it is possible to make proposals that take into account physiological information factors that are factors in lip color information. becomes possible. Therefore, in this method, for example, information belonging to the physiological information category in which the subject's lip physiological characteristics or the subject's age is a factor is also used to evaluate the lip.

Next, each factor used in this lip evaluation method and each category to which each factor belongs will be described.
Table 2 shows the category of each factor in this embodiment.

As shown in Table 2, in the present embodiment, a "physiological information category" whose factors are the physiological characteristics of the subject's lips or body, and a "sensory information category" whose factors are sensory characteristics of the subject's lips or body ” and a “color information category” whose factors are color information related to the lips or body of the subject. The "physiological information category", the "sensibility information category" and the "color information category" each include a lip-related factor and a non-lip-related factor. In this embodiment, there are a "physiological information category", a "sensibility information category", and a "color information category" as major categories, and a "pigment category" and a "blood flow category" belonging to the "physiological information category" as intermediate categories. , "Vessels Category", "Shape Category", "Surface Shape Index Category", "Color Type Category", "Body Category", "Age Category", "Gender Category", and "Kansei Information Category". Category", "Lip Tactile Category", "Lip Somatosensory Category", "Body Visual Sensation Category", "Body Tactile Category" and "Body Somatosensory Category", "Lip Color Category" belonging to "Color Information Category" And it is also said that there is a "body color category".
In addition, although the details will be described later, the factors belonging to the middle classification category are, for example, for each factor, in addition to those composed of one element such as the measured value itself, in addition to the numerical range (for example, age, teens , 20s, etc.), and the degree of feeling (for example, if it is a complexion, it is very applicable/applicable/not applicable). good. When a factor consists of multiple elements, the numerical range set for each factor is composed of multiple elements that indicate the degree of the factor. In addition to the grade consisting of multiple elements that indicate the degree of the factor, for example, in the case of each factor belonging to the color type category, the grade consists of each element determined by visual evaluation (multiple elements that classify the factor configured), etc.

A "physiological information category" is a category to which physiological characteristic factors of a subject's lips and the subject's body belong. In this embodiment, the factors of physiological characteristics are further classified into categories for each characteristic. "Pigment Category" with lip pigment information as a factor, "Blood Flow Category" with lip blood flow information as a factor, "Vessel Category" with lip blood vessel information as a factor, and "Vessels Category" with lip shape information as a factor ``Surface shape index category'' with lip surface shape index information as a factor, ``Color type category'' with lip color group information as a factor, and ``Physiological features of the subject's body as a factor "category", "age category" with the subject's age information as a factor, or "sex category" with the subject's sex information as a factor.

The “pigment category” includes factors of indicators (pigment information) relating to the types and amounts of pigments on the lips. Since the appearance of the lip color changes depending on the type and amount of pigment, it is naturally correlated with the factors of the lip color category (such as L ^* ). belongs to In this embodiment, MI (melanin index) and EI (Erythma index) belong to the pigment category.
MI is an index that roughly corresponds to the amount of melanin.
EI is an index that roughly corresponds to the amount of hemoglobin.
For example, if the MI is low, lip color will be more dependent on hemoglobin content characteristics.
For each factor belonging to the pigment category, in addition to the measured value itself, a numerical range is set for each factor, and each range is configured as an element.

"Blood flow category" includes MBR (Mean Blur Rate): blood flow, Fluctuation: fluctuation rate of blood flow, Skew: deviation of blood flow waveform, BOS (Blowout Score): steady flow of blood, BOT (Blowout Time) : Sustainability of high blood flow, Rising rate: Time variation of blood flow rising speed, Falling rate: Time variation of blood flow falling speed, FAI: Maximum rising acceleration when blood flow rises, ATI: Blood flow peak position, RI ( Resistivity Index): Peripheral vascular resistance belongs. For each factor belonging to the blood flow category, in addition to the measured value itself, a numerical range is set for each factor, and each range is configured as an element.

MBR is a relative blood flow, for example, a value obtained by applying an average MBR value to a linear regression equation, blood flow mL/(min·100 g)=41.7×MBR value−15.1.
Fluctuation is an index indicating the coefficient of variation of MBR.
Skew is a value indicating the bias of the blood flow waveform.
BOS is a value indicating a steady flow of blood.
BOT is an index indicating the persistence of a high MBR value, and the BOT value is the half width (time) (W) and one heart beat width (time) (F) of the MBR value shown in FIG. C” is expressed by the following formula.
(BOT)=C・(W)/(F)
Rising rate is an index that indicates temporal fluctuations in blood flow increasing speed.
Falling rate is an index that indicates the time variation of the falling speed from the maximum MBR value in the time waveform of the MBR value per heartbeat. Using (Sall) and (S2) shown in FIG. 6, Fallin rate can be expressed by the following equation. "C" below is the constant of proportionality.
(Falling rate)=C.(S2)/(Sall)
FAI indicates the maximum instantaneous blood flow when the blood flow increases.
ATI is the ratio of the time taken to reach the maximum MBR value (MBRmax in FIG. 6) of the MBR time waveform in one heartbeat.
RI is an index showing peripheral vascular resistance, and the RI value is obtained by dividing the difference between the maximum MBR value (MBRmax in FIG. 6) and the minimum MBR value (MBRmin in FIG. 6) by the maximum MBR value.

The "blood vessel category" belongs to area, width, length, density and branching, which are information related to blood vessels of the lips. For each factor of area, width, length, density, and branching, in addition to the measured values themselves measured from lip image data, etc., a numerical range is set for each factor, and each range is configured as an element.

The "shape category" belongs to the upper lip white lip warp width, the upper lip white lip length, the lower lip red lip swelling width, and the red lip vertical and horizontal widths. FIG. 7 is a diagram showing parts such as length and width of each factor of the shape category. For the factors belonging to the shape category, in addition to the value of each part shown in FIG. 7, a numerical range is set for each factor, and each range is configured as an element. Although not shown in Table 2, a thin lip type, a thick lip type, a thick upper lip type, and a thick lower lip type may be used.

The "surface shape index category" belongs to wrinkle-derived and peel-derived. The wrinkle origin is a value obtained from the depth, length, width, etc. obtained from surface unevenness information. The origin of skin peeling is a value obtained from non-uniformity of fine irregularities on the surface. For the factors belonging to the surface shape index category, numerical ranges are set for each factor in addition to the obtained values themselves, and each range is configured as an element.

The "color type category" includes the above-mentioned color group A consisting of the "pink type" element, the "pale type" element, the "purple type" element, and the "brown type" element, as well as the dark pink type element and the light pink The color pink group consisting of type elements belongs. In the present embodiment, the determination of the elements constituting each color group, which is each factor, is performed, for example, by colorimetric L ^* and a ^* belonging to the lip color category (the larger the positive value, the redder, and the larger the negative value, the greener). and b ^* (a larger positive value indicates a yellower color, a larger negative value indicates a bluer color, and a higher absolute value indicates a brighter color). ), C ^* and h values, and Age belonging to the age category. ^As described above, the ^lip color becomes less ^{reddish and} approaches brown with age. , is preferably determined in consideration of a factor belonging to the age category (Age). Since the factor of the age category included in the physiological information category is used to determine the elements of each color group of the color type category, the "color type category" is included in the physiological information category in this embodiment. Note that if only the appearance color (only the lip color category factor (L ^*, etc.)) is used to determine the elements of each color group without using the age category factor, the color group A may be included in the lip color category.

The “physical category” is a category to which physical information-related factors such as height, weight, BMI (Body Mass Index), blood pressure, and heart rate belong. In addition to the obtained value itself, a numerical range is set for each factor, and each range is configured as an element.
"Age category" belongs to age itself and age (20s, 30s, etc.), and when age is a factor, for example, 20s, 30s, 40s, etc. are the elements that make up the age. . ”
The “gender category” uses gender as a factor, and the elements constituting gender may include not only male and female, but also masculine and feminine elements.

The "sensory information category" is a category to which factors of sensory characteristics relating to the subject's lips and the subject's body belong. In this embodiment, a category is further provided for each feature of the factor of the sensibility feature. "Lip Visual Category" with visual information as a factor for lips, "Lip Tactile Category" with tactile information as a factor for lips, and "Lip Somatosensory Category" with somatosensory information as a factor for lips , the body, especially the face, neck, and décolletage near the lips, are classified into the ``physical visual category,'' in which visual information is used as a factor; "Body touch category" or "Body somatosensory category" that uses somatosensory information as factors for the body, especially the face, neck, and décolleté near the lips.

Here, the results of an experiment conducted on the influence of lip color on physical impression (facial impression) will be described.
<Experimental method> 31 evaluators (8 people in their 20s, 10 people in their 30s, 6 people in their 40s, 7 people in their 50s: 17 men, 14 women)
Method: Stimulus pairs created from the average face were presented on a PC monitor and evaluated using Scheffe's paired comparison method (Ura's modified method). Evaluation items: 1) Bright complexion 2) Good complexion 3) Beautiful skin 4) ) Evaluation of attractiveness on a 5-point scale Stimulus: 7 stimulus images obtained by changing only the lip color from the average face in the 40s (original image) by ±5 based on the L ^* , a ^* , b ^* color system. The facial colors of the images A to G are all the same, and only the color of the lips is changed.
FIG. 8 shows experimental results.

From FIG. 8, for example, it is clear that when the L ^* value of the lips is increased, the complexion feels “brighter”, and when the ^{L* value} of the lips is decreased, the complexion does not feel brighter. It can be said that there is a relationship between whether a person feels bright or not. Similarly, for example, when the lip a ^* value is increased, the complexion feels “brighter”, and when the lip ^{a* value} is decreased, it is clear that the complexion does not feel brighter. It can be said that it is related whether you feel it or not.
Similarly, for example, it is clear that if the L ^* value of the lips is decreased, the complexion is “improper”, and it can be said that there is a relationship between the L ^* value of the lips and whether the complexion is perceived well. Similarly, it is clear, for example, that increasing the lip a ^* value makes the complexion “feel better” and decreasing the lip ^{a* value} makes the complexion “poor”. It can be said that there is a relationship between whether or not you feel well.
Similarly, for example, if the L ^* value of the lips is reduced, it is clear that the skin does not feel "beautiful", and it can be said that there is a relationship between the L ^* value of the lips and whether the skin feels beautiful. Similarly, for example, it is clear that if the a ^* value of the lips is increased ^, the skin “feels beautiful”, and if the a ^* value of the lips is decreased, the skin “does not feel beautiful”. It can be said that there is a relationship between whether or not the skin feels beautiful.
Similarly, for example, it is clear that if the L ^* value of the lips is small, it is "unattractive", and it can be said that there is a relationship between the L ^* value of the lips and whether or not the person feels attractive. Similarly, for example, it is clear that if the a ^* value of the lips is increased, it is felt attractive, and if the ^{a *} value of the lips is decreased, it is “unattractive”. It can be said that it is related whether you feel it or not.
In this way, it is clear that there is a relationship between the lip color (lip color category) and the body visual perception category. are different.

The "visual lip category" includes factors such as complexion, transparency, bright color, good color, beautiful and attractive. The sense of complexion is how the subject himself/herself or another subject feels the complexion when looking at the lips, for example, the complexion looks good (fits) / does not look good (looks bad (does not fit) ). Transparency is how a subject or another subject perceives translucency when looking at the lips, e.g., appear translucent (true)/do not appear translucent (not true) , consists of elements of Lightness of color is how subjects themselves or other subjects perceive lightness of color when looking at their lips, and is composed of factors such as whether the color appears light (it fits) or does not. . Good color is how the subject or other subjects perceive the color to be good when looking at the lips, e.g. ). Pretty is how the subject himself/herself or another subject feels about beauty when looking at the lips, and is composed of, for example, the element of looks beautiful/does not look beautiful (doesn't apply). Attractiveness is how subjects perceive themselves or other subjects in terms of attractiveness when looking at their lips, e.g. , consists of elements of In the present embodiment, all the factors included in the visual sensation category are composed of two elements of fitting/not fitting. It may be composed of three elements: Also, some factors may be composed of two elements and other factors may be composed of three elements.

The "lip feel category" includes factors such as roughness and elasticity. Roughness is composed of the subject's own or another subject's perception of roughness when touching the lips (true)/no perception of roughness (non-true). Elasticity is composed of elements of feeling elasticity (applicable)/not feeling elasticity (not applicable) when the subject himself or another subject touched the lips. In the present embodiment, all factors included in the tactile category are composed of two elements of fit/not fit, but not limited to this, all factors are very fit, fit, and not fit. It may be composed of three elements: Also, some factors may be composed of two elements and other factors may be composed of three elements.

The lip somatosensory category includes factors such as tightness and dryness. The feeling of tightness is composed of elements that the subject himself/herself felt that the lips were tight (applicable)/did not feel (disagreeable). The feeling of dryness is composed of elements that the subject himself/herself felt that the lips were dry (applicable)/not felt (not applicable). In the present embodiment, all the factors included in the somatosensory category are composed of two elements of fit/not fit, but not limited to this, all factors are very fit, fit, fit It may be composed of three elements: Also, some factors may be composed of two elements and other factors may be composed of three elements.

The "physical visual perception category" includes factors such as complexion, transparency, bright color, good color, beauty and attractiveness. The sense of complexion is how the subject himself/herself or other subjects feel about complexion when looking at the body. ). Transparency is how the subject perceives transparency when looking at the body itself or other subjects, e.g., appears transparent (true) / does not appear transparent (disagree) , consists of elements of Light color is how the subject or other subjects perceive the light color when looking at the body, and is composed of factors such as appearing (true) or not seeing the color bright. . Good color is how the subject or other subjects perceive the color to be good when looking at the body, e.g. ). Pretty is how the subject himself/herself or another subject feels about beauty when looking at the lips, and is composed of, for example, the element of looks beautiful/does not look beautiful (doesn't apply). Attractiveness is how subjects perceive themselves or other subjects in terms of attractiveness when looking at their body, e.g. , consists of elements of In the present embodiment, all factors included in the body visual perception category are composed of two elements of fit/not fit, but not limited to this, all factors are very fit, fit, fit It may be composed of three elements: Also, some factors may be composed of two elements and other factors may be composed of three elements.

The "physical feel category" includes factors such as roughness and elasticity. Roughness is composed of the subject's or another subject's sense of grittiness when touching the body (true)/no sense of grittiness (not true). Elasticity is composed of elements of feeling elastic (applicable) / not feeling elastic (non-applicable) when the subject or another subject touches the body. In the present embodiment, all the factors included in the physical sensation category are composed of the two elements of applicable/not applicable, but not limited to this, all factors are very applicable, applicable, and applicable. It may be composed of three elements: Also, some factors may be composed of two elements and other factors may be composed of three elements.

The "body somatosensory category" includes factors such as tightness and dryness. The feeling of tightness is composed of elements that the subject himself/herself felt (applicable)/did not (disagree) with respect to the body. The feeling of dryness is composed of elements that the subject himself/herself felt dry (applicable)/did not feel (not applicable). In the present embodiment, all the factors included in the body somatosensory category are composed of two elements that apply / do not apply, but not limited to this, all factors are very applicable, apply, It may be composed of three elements that do not apply. Also, some factors may be composed of two elements and other factors may be composed of three elements.

"Color information category" is a category to which information factors for identifying the type of color based on colorimetric values or colorimetric values of the subject's lips and body belong. Further, a "lip color category" having color information about the lips as a factor and a "body color category" having color information about the body, especially the face, neck and décolleté close to the lips as factors, are provided.

The lip color category is a category to which the lip colorimetric value or the information factor for specifying the color type based on the colorimetric value belongs. In this embodiment, the following factors belong to the lip color category.
L ^* is lightness.
For a ^* , a larger positive value indicates a reddish direction, and a larger negative value indicates a greener direction.
A larger positive value of b ^* indicates a yellower direction, and a larger negative value of b* indicates a bluer direction.
C ^* is the saturation.
h is the hue.
R is a value related to the intensity of long wavelengths (red region) in RGB, which is a kind of color expression.
G is a value related to the intensity of medium wavelengths (green region) in RGB, which is a kind of color expression.
B is a value related to the intensity of short wavelengths (blue region) in RGB, which is a kind of color expression.
The spectral spectrum is a relative value representing the ratio of monochromatic content.
A color sample is a list of color samples created according to a predetermined standard.
The color difference is a value representing the difference in color, for example, a value representing the difference between the red lip portion and the white lip portion.
Color unevenness indicates spatial non-uniformity of color, and is a value obtained from frequency, histogram shape (dispersion, skewness, kurtosis, etc.), statistics, and the like.

The body color category is a category to which a body colorimetric value or an information factor for specifying a color type based on the colorimetric value belongs. In this embodiment, the factors belonging to the body color category are the same as those of the lip color category, so the explanation is omitted.

The factors listed in Table 2 are those in this embodiment, and other factors may be included.

This method will be described.
"Physiological information category whose factors are the physiological characteristics of the subject's lips or body" is a category to which the subject's lip and physiological characteristics of the subject's body belong, and the lip pigment information is the factor. "Pigment category", "blood flow category" with lip blood flow information as a factor, "blood vessel category" with lip blood vessel information as a factor, "shape category" with lip shape information as a factor, lip surface shape "Surface shape index category" with index information as a factor, "Color type category" with lip color group information as a factor, "Physical category" with physiological characteristics of the subject's body as a factor, and subject's age information as a factor Includes "age category" as a factor or "gender category" as a factor of subject's gender information.
"A sensory information category whose factors are the sensory features of the subject's lips or body" is a category to which the sensory feature factors of the subject's lips and body belong. ``Lip visual sensation category'' with tactile information as a factor for the lip, ``Lip tactile sensation category'' with somatosensory information as a factor for the lip, the body, especially the lips "Physical visual sensation category" for the face, neck and décolleté, which is based on visual information, and "body tactile category", which is based on tactile information for the body, especially the face, neck, and décolleté near the lips, or the body, especially , the face, neck, and décolletage near the lips are included in the ``body somatosensory category'' that uses somatosensory information as factors.
"Color information category whose factor is color information related to the lips or body of the subject" means the colorimetric value of the subject's lips and body or information for identifying the type of color based on the colorimetric value This category includes the "Lip color category" whose factors are color information related to the lips and the "Body color category" whose factors are color information related to the body, especially the face, neck and décolletage close to the lips.
"Category group" includes "pigment category", "blood flow category", "vessel category", "shape category", "surface shape index category", "color type category", and "body category" included in the physiological information category. Categories", "Age Category", "Gender Category", "Lip Visual Category", "Lip Tactile Category", "Lip Somatosensory Category", "Body Visual Category", "Body It consists of a "tactile sensation category", a "bodily somatosensory category", and a "lip color category" and a "body color category" included in the color information category. "From the category group, use multiple factors including one or more factors belonging to the physiological information category as input factors," means that one or more factors belonging to the physiological information category and factors belonging to other categories are used as input factors. Alternatively, two or more factors belonging to the physiological information category may be used as input factors, or a plurality of factors may all belong to the physiological information category.
"Evaluate the subject's lip or body characteristics by using a factor different from the input factor as an output factor" means that if a factor different from the input factor is output as an output factor, the category to which the input factor belongs and the category to which the output factor belongs may be the same or different. In addition, according to the calculated output factor, evaluation of external aspects such as the characteristics of the subject's lips or body, such as color and appearance, and evaluation of internal aspects such as blood flow are performed.
"Mathematical model obtained in advance from a population and showing the correlation between multiple input factors and output factors" is information obtained by obtaining information on each factor in advance from a population consisting of multiple subjects. is a mathematical model showing the relationship between multiple input factors and output factors created from Mathematical model is a single element or a mathematical model that outputs the value of a single element. , regression trees, etc. Mathematical models that output multiple elements and ratios of multiple elements include naive Bayes classifiers, gradient boosting, support vector machines, neural networks, and deep learning.
"Determining the output factor based on the plurality of input factors obtained from the subject" means determining the above-described output factor based on the above-described input factor and the mathematical model.

Next, an overview of the processing flow of this method will be described with reference to FIG. Although the details will be described later, FIG. 9 shows, for the output factor obtained by this processing, the value of one element of the corresponding output factor or the value of one element of the corresponding output factor, the multiple elements of the corresponding output factor, and the ratio of the multiple elements. It is a processing flow in which both are required, but only one of them may be required. In this embodiment, obtaining the value of one element or one element of the relevant output factor is called "deterministically obtaining", and obtaining the ratio of multiple elements and multiple elements of the relevant output factor is called " It is sometimes described as "calculated as a percentage". In addition, FIG. 9 shows that the output factor is calculated by using a predetermined mathematical model to calculate one element or the value of one element, and by using a predetermined mathematical model to calculate a plurality of elements and a ratio of the plurality of elements. is shown. In the present embodiment, calculating one element or the value of one element using a predetermined mathematical model is called "calculating in simple mode", and calculating a plurality of elements and a ratio of a plurality of elements is " It is sometimes written as "calculate in polite mode".

The step (step S100) is a step of determining input factors and output factors. In this method, a plurality of factors including those included in the lip physiological information category are used as input factors, and factors different from the input factors can be output. Therefore, an input factor and an output factor are determined, and an output factor is obtained based on the determined input factor. Input factors and output factors may be determined in any combination and in any kind, but the accuracy of the output factors obtained differs depending on the input factors. Therefore, it is preferable that the combination and type of input factors with high accuracy are determined automatically or as recommended factors by determining desired output factors.

The step (step S110) is to obtain an output factor of one element or a value of one element, or to obtain a plurality of elements and a ratio of a plurality of elements as an output factor, in other words, to calculate in a simple mode, or to calculate in a polite mode Decide whether to calculate This step may be automatically determined according to the desired output factor. When obtaining the output factor of one element or the value of one element, the process proceeds to step S120. When obtaining the output factors of a plurality of elements and the ratio of the plurality of elements, the process proceeds to step S130.

The step (step S120) uses the input factor determined in step S100 and the mathematical model for obtaining the output factor of one element or one element value when it is decided to obtain the output factor in the simple mode in step S110. This is the step of obtaining the output factor by A mathematical model represents the relationship between input factors and output factors from a population.

A step (step S130) uses the input factors determined in step S100 and the mathematical model for determining the plurality of elements and the ratio of the plurality of elements when it is determined in step S110 to obtain the output factors in the polite mode. This is the step of obtaining the output factor. A mathematical model represents the relationship between input factors and output factors from a population.

In the step (step S140), using the plurality of elements and the ratio of the plurality of elements obtained in step S130 as they are, for example, a recommended care method or makeup method is proposed, or the obtained plurality of elements and the ratio of the plurality of elements are proposed. This is a step of identifying one output factor based on the ratio and proposing or determining a recommended care method or makeup method using the identified output factor. This step may be automatically determined according to the desired output factor. Further, it is preferable to determine which output factor to use depending on how the output factor is used (proposal of care method, proposition of makeup products, etc.).

The step (step S150) is a step of specifying a single-element output factor when it is determined to specify a single-element output factor in step S140. The specifying method corresponds to specifying the output element with the highest/lowest ratio, specifying by the staff at the store or the like, or by the user.

The step (step S160) is a step of proposing care methods, makeup products, etc., based on the output factors obtained in step S120, step S130, or step S150. Note that this step is a step that utilizes the output factor obtained by this method, and therefore is not included in this method. Steps S110 and S140 may also be determined automatically by determining the input factor and the output factor in step S100, and thus may not be included in the present method. Further, the method may be either simple/polite mode.

Next, the lip evaluation performed by this method will be described. Note that the implementation pattern shown below is an example. Implementation patterns 1 to 3 are polite mode examples in which a Gaussian Naive Bayes model is used as a mathematical model that indicates the correlation between multiple input factors and output factors, and multiple elements and ratios of multiple elements are obtained as output factors. is. Further, implementation patterns 4 to 6 are examples of a simple mode in which a multiple regression equation is used as a mathematical model showing the correlation between a plurality of input factors and output factors to obtain an output factor of one element or a value of one element. . Each mathematical model was created in advance using the measured values of the factors shown in Table 2 for the population of 85 people described in FIG. When the factor of the color information category is used as the input factor, the measurement value of the user's bare lips is used. By doing so, it is possible to accurately evaluate the user's lips. In addition, when a color group (color type) is used as an input factor, the color type that is calculated in advance from the measured values of the factors in the color information category and the measured values of the factors included in the physiological information category is used. Just do it. Also, the factor belonging to the shape category may be obtained by obtaining a user's lip image in advance and measuring the size of each part from the lip image.

<Implementation pattern 1>
FIG. 10 shows an outline of implementation pattern 1. As shown in FIG.
In implementation pattern 1, based on a Gaussian naive Bayes model created using measured values of a population (85 people in this embodiment), elements belonging to color group A of the color type category: pink type, pale type, purple type , and the degree of each possibility of Brown type, the ratio was calculated. In implementation pattern 1, the user's measurement values (three variables) of C ^* belonging to the lip color category of the color information category, and MI belonging to the pigment category of h and the physiological information category were used as input factors. That is, a factor belonging to the pigment category of the physiological information category (e.g., corresponding to MI) and a factor belonging to the lip color category of the color information category (e.g., corresponding to C ^* and h) are used as input factors. (for example, color group A: corresponding to pink type, pale type, purple type, and brown type) were obtained as output factors.
As shown in FIG. 10, the generalization performance for the test data in this model was high with a correct answer rate of 0.88 (88%). In addition, the evaluation of the classification performed in this model also resulted in the highest rate of being classified into the desired factor.
Then, as a result of calculating the output factor using the user's measured values (C ^* : 20, h: 40, MI: 45) for this input factor and a mathematical model, the ratio of the plurality of elements belonging to color group A is pink type, A high possibility of belonging to the order of brown type, pale type, and purple type was sought. Using this result, for example, when recommending makeup products (lipstick), it is possible not only to propose makeup products suitable for pink-type users, but also to recommend makeup products suitable for brown-type users. You can make a proposal to that effect. By making such a proposal, if the user prefers (preferred color) makeup products suitable for brown type users to makeup products suitable for pink type users, the user may choose brown type makeup products. Since it becomes easier for the user to select makeup products suitable for the user, it is possible to make an appropriate proposal. Further, in the case of implementation pattern 1, since the possibility that the user's color type is the purple type is the lowest, it is possible to suggest that it is better not to select makeup products suitable for the purple type. As described above, since there is no clear boundary between lip color types, by obtaining color types with high probability as in implementation pattern 1, for example, only one specific color type is obtained, and that color It is possible to make a proposal suitable for a lip color type without a clear boundary, compared to the case of making a proposal of makeup products or a care method according to the type.
In this way, using a mathematical model, a plurality of factors belonging to one category based on the input factor (in the case of implementation pattern 1, a plurality of elements belonging to color group A of the color type category) are Classify and output according to the corresponding ratio.

<Implementation pattern 2>
FIG. 11 shows an outline of implementation pattern 2. As shown in FIG.
In implementation pattern 2, based on a Gaussian Naive Bayes model created using measured values of a population (85 people in this embodiment), elements belonging to color group A of the color type category: pink type, pale type, purple type , the ratio of each possibility of Brown type was obtained. Implementation pattern 2 is user measurements of L ^* , a ^* , b ^* , C ^* , and h belonging to the lip color category of the color information category, Age belonging to the age category of the physiological information category, and MI and EI belonging to the pigment category. Values (8 variables) were used as input factors. That is, factors belonging to the physiological information category (for example, Age, MI and EI) and factors belonging to the lip color category of the color information category (for example, L ^* , a ^* , b ^* , C ^* , and h) are input factors. , and the factors belonging to the color type category included in the physiological information category (for example, color group A: corresponding to pink type, pale type, purple type, and brown type) were obtained as output factors.
As shown in FIG. 11, the generalization performance for the test data in this model was high with a correct answer rate of 0.76 (76%). In addition, the evaluation of the classification performed in this model also resulted in the highest rate of being classified into the desired factor.
And using this input factor (L ^* : 43, a ^* : 14, b ^* : 15, C ^* : 20, h: 40, Age (age): 20, MI: 45, EI: 73) and a mathematical model As a result of obtaining the output factors, it was found that the ratio of the plurality of elements belonging to the color group A was highly likely to belong to the pale type, pink type, brown type, and purple type in that order. Using this result, for example, when recommending makeup products (lipstick), it is possible not only to propose makeup products suitable for pale-type users, but also to recommend makeup products suitable for pink-type users. You can make a proposal to that effect. By making such a proposal, if the user prefers makeup products (favorite color) suitable for pink type users to makeup products suitable for pale type users, the user may find that the user prefers pink type makeup products. Since it becomes easier for the user to select makeup products suitable for the user, it is possible to make an appropriate proposal. Moreover, in the case of implementation pattern 2, since there is almost no possibility that the user's color type is the purple type, it is possible to suggest that it is better not to select makeup products suitable for the purple type. As described above, since there is no clear boundary between lip color types, by obtaining color types with high possibility as in implementation pattern 2, for example, only one specific color type is obtained, and that color It is possible to make a proposal suitable for a lip color type without a clear boundary, compared to the case of making a proposal of makeup products or a care method according to the type.
In this way, using a mathematical model, a plurality of elements belonging to one of the categories (in the case of implementation pattern 2, a plurality of elements belonging to color group A of the color type category) based on the input factors are Classify and output according to ratio.

<Implementation pattern 3>
FIG. 12 shows an outline of implementation pattern 3. As shown in FIG.
In implementation pattern 3, based on the Gaussian Naive Bayes model created using the measured values of the population (85 people in this embodiment), the ages belonging to the age category of the physiological information category: 20s, 30s, 40s, We calculated the percentage of each possibility of people in their 50s, 60s, and 70s.
Implementation pattern 3 is user measurement of L ^* and C ^* belonging to the lip color category of the color information category, MBR, Skew, ATI, and RI belonging to the blood flow category of the physiological information category, and MI and EI belonging to the pigment category. Values (8 variables) were used as input factors. As shown in FIG. 12, the generalization performance for the test data in this model was a correct answer rate of 0.47 (47%). In addition, the evaluation of the classification performed in this model resulted in the highest rate of classification into the elements desired to be classified. And this input factor (L ^* : 44.824 and C ^* : 21.41, MBR: 1624.2, Skew: 11.8, ATI: 27.3, RI: 0.29, MI: 39.934 , EI: 79.575) and a mathematical model, the output factor was found to be significantly higher in the 40s and lower in the 30s and 20s. Since the actual age of this user is 42 years old, it can be said that the value of the element of the output factor is highly accurate. Using this result, for example, when suggesting recommended makeup products (lipstick), not only makeup products suitable for users in their 40s but also makeup products suitable for users in their 30s and 20s are proposed. It is possible to make a proposal to the effect that it can also be recommended. By making such a proposal, if the user prefers makeup products (favorite colors) suitable for users in their 30s and 20s over makeup products suitable for users in their 40s, the user can Since it becomes easier for users in their thirties and twenties to select makeup products suitable for them, it is possible to make appropriate proposals. In the case of implementation pattern 3, since there is no possibility that the user's age is in their 50s, 60s, or 70s, it is better not to select makeup products suitable for people in their 50s, 60s, and 70s. It is also possible to propose
In this way, using a mathematical model, multiple factors belonging to one of the categories based on the input factors (in the case of implementation pattern 3, multiple elements belonging to the age category) are classified according to the corresponding ratio. and output.

<Implementation pattern 4>
FIG. 13 shows an outline of implementation pattern 4. As shown in FIG.
In implementation pattern 4, the age belonging to the age category of the physiological information category was obtained based on the multiple regression equation created using the measured values of the population (for 85 people in this embodiment). The input factors in multiple regression equation were selected based on domain knowledge.
Implementation pattern 4 includes L ^* , C ^* , and h belonging to the lip color category of the color information category, and factors belonging to the color type category of the physiological information category (for example, color group A: pink type, pale type, purple type and Brown type) were used as input factors. That is, factors included in the color type category of the physiological information category (for example, color group A: corresponding to pink type, pale type, purple type, and brown type), and multiple factors belonging to the lip color category of the color information category (L ^* , C ^* , and h) were used as input factors, and factors included in an age category different from the category to which the input factors belong (for example, corresponding to Age) were obtained as output factors.
As shown in FIG. 13, the coefficient of determination (R ² ) by this multiple regression equation was 0.64, and it was clear that there was a strong correlation. Therefore, by inputting the user's measured values corresponding to the input factors to the explanatory variables of the multiple regression equation shown in FIG. 13, it is possible to obtain the user's age with high accuracy.
It should be noted that factors included in the age category output in implementation pattern 4 are limited to age information.

<Implementation pattern 5>
FIG. 14 shows an outline of implementation pattern 5. As shown in FIG.
In implementation pattern 5, an MI (melanin index) belonging to the pigment category of the physiological information category was determined based on a multiple regression equation created using measured values of a population (for 85 people in this embodiment). Variables in multiple regression equations were selected with domain knowledge.
In implementation pattern 5, L ^* , C ^* , and h belonging to the lip color category of the color information category and the user's measurement values (4 variables) of Age belonging to the age category of the physiological information category were used as input factors. That is, a factor belonging to the age category (for example, Age corresponds) and a plurality of factors belonging to the lip color category of the color information category (for example, L ^* , C ^* , and h) are used as input factors, and the physiological information category A factor included in (for example, corresponding to MI) was obtained as an output factor. MI obtained as an output factor belongs to the pigment category of the physiological information category, and the lip color category of the color information category to which L ^* , C ^* , and h used as input factors belong, and the physiological information category to which Age belongs. is a factor belonging to a category different from the age category of , and the output factor belongs to a category different from the category to which the input factor belongs. The "different categories" include the above-mentioned pigment category, blood flow category, blood vessel category, shape category, surface shape category, color type category, body category, age category, gender category, lip visual sensation category, lip touch category, The category to which the input factor belongs differs from the category to which the output factor belongs for the lip somatosensory category, the body visual sense category, the body tactile sense category, the somatosensory category, the lip color category, or the body color category.
As shown in FIG. 14, ^R2 by this multiple regression equation was 0.92, and it was clear that there was a correlation. Therefore, by inputting the user's measured values corresponding to the input factors as explanatory variables of the multiple regression equation shown in FIG. 14, it is possible to obtain the user's MI.

<Implementation pattern 6>
FIG. 15 shows an outline of implementation pattern 6. As shown in FIG.
In implementation pattern 6, EIs belonging to the pigment category of the physiological information category were obtained based on multiple regression equations created using measured values of a population (for 85 people in this embodiment). Variables in multiple regression equations were selected based on domain knowledge.
Implementation pattern 6 includes FAI belonging to the blood flow category of the physiological information category, factors belonging to the color type category of the physiological information category (for example, color group A: corresponding to pink type, pale type, purple type, and brown type), and , measured values (three variables) of the user's height belonging to the physical category of the physiological information category are used as input factors, and factors included in the physiological information category (for example, EI) are determined as output factors. That is, a plurality of factors including one or more factors belonging to the physiological information category from the physiological information category and the physical category were used as input factors. In addition, EI obtained as an output factor belongs to the pigment category of the physiological information category, and is different from the blood flow category to which FAI used as the input factor belongs, the color type category to which color group A belongs, and the body category to which height belongs. It is a factor belonging to a category.
As shown in FIG. 15, ^R2 by this multiple regression formula was 0.57, and it was clear that there was a correlation. Therefore, by inputting the user's measured values corresponding to the input factors to the explanatory variables of the multiple regression equation shown in FIG. 15, it is possible to obtain the user's EI.

As described above, the method can determine different output factors based on different input factors and different mathematical models. As in implementation patterns 1 to 3, by obtaining a plurality of elements and the ratio of the elements and determining which element has the highest probability, or which element has a certain probability, When proposing a makeup product or a care method using the obtained result, a more appropriate proposal can be made than when only one element is obtained. On the other hand, as in implementation patterns 4 to 6, it may be appropriate to obtain one element depending on the type of factor. In this manner, the input factors and the mathematical model may be determined according to how the desired output factors and the determined output factors are to be used. Also, for example, even if there are no user-measured values for all the factors shown in Table 2, it is possible to obtain a predetermined factor as an output factor.

<Lip evaluation system 10>
A lip evaluation system 10 that executes the lip evaluation method described above and evaluates the characteristics of the subject's lips or body using a factor different from the input factor as an output factor will be described. FIG. 16 shows a conceptual diagram of the lip evaluation system 10. As shown in FIG.
A lip evaluation system 10 (hereinafter, also referred to as this system) is an information processing terminal capable of executing various processes, and includes a storage unit 11, an input unit 12, a calculation unit 13, an output unit 14, and an evaluation unit 15. . Although not shown, the lip evaluation system 10 includes an input device such as a keyboard pointing device, an arithmetic processing device, a storage section, a display device, and the like.

The storage unit 11 is storage means for storing a mathematical model obtained in advance from a population and indicating the correlation between a plurality of input factors and output factors. In addition to the mathematical model, it also stores the programs and data necessary to carry out the method.
The input unit 12 is input means for inputting a plurality of input factors obtained from subjects. An input device provided in an information processing terminal corresponds.
The calculation unit 13 is calculation means for obtaining output factors based on the mathematical model and the input factors. It corresponds to an arithmetic processing unit provided in an information processing terminal.
The output unit 14 is output means for outputting the calculated output factor. In addition to outputting to a display device provided in an information processing terminal, outputting to a device or system different from the lip evaluation system 10 and outputting to a printer are also included.
The evaluation unit 15 is evaluation means that uses output factors to propose makeup products and lip care products, and to propose makeup methods and care methods. It corresponds to an arithmetic processing unit provided in an information processing terminal. According to the output factor obtained by the calculation unit 13, for example, a recommended lip cosmetic is extracted from a plurality of lip cosmetics having different color patterns and is proposed, or a recommended lip care method is selected from among a plurality of lip care methods. are extracted and proposed.

Here, a lip cosmetic recommended when a ratio corresponding to each of the plurality of elements constituting the color group A factor is obtained as an output factor from implementation pattern 1 or 2 will be described. Lip cosmetics recommended in the present embodiment are lip cosmetics (makeup products) to be applied to the lips, such as lipstick, colored lip balm, lip gloss, lip pencil, lip liner, and powder lip.
Table 3 shows recommended makeup product types by color type.

Makeup products are intended to be enjoyed by changing the color of the lips beautifully, but as a general finish, redness is often imparted in order to make the face look good. In the present embodiment, a makeup product is proposed for the purpose of imparting redness by applying the makeup product to the bare lips.
The pink type has a bright red lip color, so it doesn't matter what type of makeup you choose. It is sufficient to suggest that the user select makeup products according to his/her preference.
Since the pale type has a lip color that is not reddish, even if you apply makeup with low-coverage makeup, it will be the color of your bare lips, that is, a lip color that is not reddish. Not recommended.
Since the purple type has a low-saturation lip color, even with low-saturation makeup products and low-coverage makeup products, the color of the bare lips, that is, the low-saturation, non-reddish lip color. Low-saturation makeup products and low-coverage makeup products are not recommended because they become colored.
Since the brown type has a dark lip color, high-brightness makeup products, low-saturation makeup products, and low-coverage makeup products can be used to make up the bare lip color, i.e., dark, non-reddish lip color. Therefore, high-brightness makeup, low-saturation makeup, and low-coverage makeup are not recommended.

Next, a recommended care method in the case where a ratio corresponding to each of the plurality of elements constituting the color group A factor is obtained as an output factor by implementation pattern 1 or 2 will be described.
Table 4 shows recommended care methods for each color type.

In general, a bright red lip color is considered to be a healthy and beautiful lip color. Lips with a vivid red color have good blood flow, blood reaches the periphery, and there is little melanin pigment. Therefore, in the present embodiment, a care method is proposed for the purpose of approximating the bright red color of the lips.
Here, care target: blood flow refers to care for improving blood flow in the lips, and includes massage, moisturizing care, hot compress, lip pack, carbonate preparation, and warming preparation. Care target: Melanin is care for reducing melanin pigment, and there are care agents, cleansing agents, UV protection agents, brightening agents, etc. that reduce melanin pigment.
The pink type has good blood flow and less melanin pigment. It should be noted that there is no problem in preventively performing blood flow care and melanin care, even if it is not necessary.
The pale type has less melanin pigment, but blood flow is poor and it is difficult for blood to reach the periphery, so blood flow care should be recommended.
The purple type has less melanin pigment, but blood flow is poor and blood does not reach the periphery, so blood flow care should be recommended.
Brown type has a lot of melanin pigment, so melanin pigment care should be recommended.

Next, the difference in the contents of makeup product proposals and care method proposals between when output factors are obtained in the polite mode and when they are obtained in the simple mode will be described.
Table 5 shows the difference in the contents of makeup product proposals and care method proposals between the polite mode and the simple mode.

In the polite mode of Table 5, when proposing makeup products, if the ratio is 60% or more, the makeup product type shown in Table 3 is recommended, and if the ratio is 30% or more and less than 60%, it is partially recommended, and 30%. Not recommended if less than It should be noted that "partially recommended" means that some of the makeup products of that type can be recommended and some cannot be recommended depending on the color. In addition, in the proposal of the care method, when the ratio is 60% or more, the care method shown in Table 4 is positively recommended, when it is 30% or more and less than 60%, it is recommended, and when it is less than 30%, it is preventive recommendation. bottom.
As is clear from Table 5, even for the same user, there are differences in the recommended makeup products and care methods between the polite mode and the simple mode. As mentioned above, there is no clear boundary between lip color types, so rather than specifying one of the multiple elements that make up the output factor, we construct the output factor when there are multiple possible color types. Proposing makeup products and care methods that are recommended according to the ratio of each of the multiple elements makes it possible to make a wide range of proposals that match the color of the lips.
Also, hypothetically, if the recommended care method based on the output factor obtained in polite mode is performed, and after a predetermined period of time, the output factor is obtained again in careful mode, if there is no change in the type of output factor (color type) However, the ratio may change. And due to changes in the ratio, recommended makeup products and care methods may also change. In this way, by obtaining the output factors in polite mode and proposing recommended makeup products and care methods based on the ratio, it is possible to make appropriate suggestions in the process of changing (improving) the color of the lips. .

<Modification>
In this embodiment, recommended makeup products are proposed based on output factors, but recommended makeup methods may be proposed based on output factors. Also, although the recommended care method was proposed based on the output factor, the recommended care product may be proposed based on the output factor.

In addition to the combination of input factors used in Implementation Pattern 1 and Implementation Pattern 2, color groups belonging to the color type category are based on a Gaussian Naive Bayes model created using measured values of a population (for 85 people in this embodiment). It is possible to calculate the ratio of the probability of each of the elements (pink type, pale type, purple type, and brown type) constituting A. Table 6 shows other examples of combinations of input factors.

The combination of 1 in Table 6 is implementation pattern 2, and the combination of 9 is implementation pattern 1. As is clear from Table 6, the generalization performance for test data is high in any combination. Also, the combinations of 7 and 8 do not use factors belonging to the physiological information category as input factors. In this way, it is possible to obtain output factors belonging to the color type category even if only factors belonging to the color information category are used as input factors. , 9 and 10) the generalization performance to the test data is high. Therefore, it is possible to perform highly accurate lip evaluation by using factors belonging to the physiological information category as input factors.

The lip evaluation system may be provided with an image capturing device for capturing an image of the user's lips, and a value to be an input factor may be measured from an image captured by the image capturing device and input. By doing so, it is possible to evaluate the state of the lips at the time when the evaluation is desired. Alternatively, a user's lip image photographed outside the lip evaluation system may be acquired, and a value serving as an input factor may be measured from the acquired image and input. By doing so, for example, a lip image photographed by the user can be transmitted to the lip evaluation system, and evaluation can be performed based on the data, so that convenience can be improved.

In the lip evaluation system of this embodiment, the value of the input factor is input by the input means, but it is not limited to this. For example, as described above, a value that is an input factor may be measured from an image captured by a photographing device or an acquired image, and may be loaded into the calculation means, and this loading process may be used as the input means.

10 lip evaluation system 11 storage unit 12 input unit 13 calculation unit 14 output unit 15 evaluation unit

Claims (10)

A physiological information category whose factors are the physiological characteristics of the subject's lips or body, a sensory information category whose factors are sensory characteristics of the subject's lips or body, and color information about the subject's lips or body as factors. from a category group consisting of color information categories, a plurality of factors including one or more of the factors belonging to the physiological information category as input factors, and the factors different from the input factors as output factors, the lips or body of the subject A method for evaluating characteristics of
wherein the output factor is determined based on a mathematical model obtained in advance from a population and indicating the correlation between the plurality of input factors and the output factor, and the plurality of input factors obtained from the subject. lip evaluation method. The physiological information category includes a pigment category with lip pigment information as a factor, a blood flow category with lip blood flow information as a factor, a blood vessel category with lip blood vessel information as a factor, and a lip shape information as a factor. shape category, surface shape index category with lip surface shape index information as a factor, color type category with lip color type information as a factor, body category with physiological characteristics of the subject's body as a factor, subject's age including an age category factored by the information or a gender category factored by the subject's gender information;
The sensibility information category includes a lip visual sensation category whose factor is the visual information of the lips, a lip tactile sensation category whose factor is the lip tactile information, a lip somatosensory category whose factor is the lip somatic sensation, Including the body-visual category with visual information as a factor, the body-tactile category with bodily tactile information as a factor, or the body-somatosensory category with bodily somatosensory as a factor,
2. The lip evaluation method according to claim 1, wherein said color information category includes a lip color category whose factor is lip color information and a body color category whose factor is body color information. A factor belonging to the physiological information category and a factor belonging to the color information category are used as the input factors,
3. The lip evaluation method according to claim 2, wherein a factor belonging to said color type category is obtained as said output factor. The input factors include the pigment category, the blood flow category, the blood vessel category, the shape category, the surface shape index category, the color type category, the body category, the age category, the gender category, and the lip visual perception category. , the lip touch category, the lip somatosensory category, the physical visual category, the physical tactile category, the somatic somatosensory category, the lip color category, or the body color category,
4. The lip evaluation method according to claim 2, wherein said output factor belongs to a category different from the category to which said input factor belongs. a plurality of factors included in the physiological information category and factors belonging to the color information category as the input factors;
5. The lip evaluation method according to claim 2, wherein a factor belonging to said age category is obtained as said output factor. a factor belonging to the age category and a plurality of factors belonging to the color information category as the input factors;
6. The lip evaluation method according to any one of claims 2 to 5, wherein a factor belonging to the physiological information category is obtained as the output factor. Each factor is composed of a plurality of elements that indicate the degree of the factor or classify the factor,
7. The method according to any one of claims 1 to 6, wherein the mathematical model is used to classify and output the plurality of elements constituting the output factor based on the input factor according to a corresponding ratio. The described lip evaluation method. 8. The lip evaluation method according to any one of claims 1 to 7, wherein a recommended lip cosmetic is extracted from a plurality of lip cosmetics having different color patterns according to the obtained output factor. . 9. The lip evaluation method according to any one of claims 1 to 8, wherein a recommended lip care method is extracted from a plurality of lip care methods according to the obtained output factor. A physiological information category whose factors are the physiological characteristics of the subject's lips or body, a sensory information category whose factors are sensory characteristics of the subject's lips or body, and color information about the subject's lips or body as factors. from a category group consisting of color information categories, a plurality of factors including one or more of the factors belonging to the physiological information category as input factors, and the factors different from the input factors as output factors, the lips or body of the subject A system for evaluating characteristics of
storage means for storing a mathematical model obtained in advance from a population and showing the correlation between the plurality of input factors and the output factors;
input means for inputting the plurality of input factors obtained from the subject;
and calculating means for obtaining the output factor based on the mathematical model and the input factor.

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