Lip evaluation method

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

[Technical Field]

[0001] The present invention relates to a method for evaluating lips. [Background technology]

[0002] There is a method for determining the lip color of a user and selecting a lipstick color that suits the user's lip color category using a lipstick selection chart based on the lip color category (Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-62042 Summary of the Invention [Problem to be solved by the invention]

[0004] 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 progressed, it became apparent that simply classifying based on color-related information such as lightness, saturation, and hue was not sufficient, and there was room for improvement.

[0005] The present invention has been made in view of the above-mentioned problems, and relates to a lip evaluation method for evaluating lips using information belonging to a physiological information category in which the physiological characteristics of the lips of a subject or the age of the subject is used as a factor. [Means for solving the problem]

[0006] The present invention relates to a method for evaluating the characteristics of a subject's lips or body by using as input factors a plurality of factors including one or more factors belonging to a physiological information category from a category group consisting of a physiological information category whose factors are physiological characteristics related to the lips or body of the subject, an affective information category whose factors are sensory characteristics related to the lips or body of the subject, and a color information category whose factors are color information related to the lips or body of the subject, and by using as output factors a factor different from the input factors, the lip evaluation method is characterized in that the output factors are determined based on a mathematical model that is obtained in advance from a population and shows the correlation between the plurality of input factors and the output factors, and on the plurality of input factors obtained from the subject.

[0007] The present invention also relates to a system for evaluating the characteristics of a subject's lips or body by using as input factors a plurality of factors including one or more factors belonging to a physiological information category from a category group consisting of a physiological information category whose factors are physiological characteristics related to the lips or body of the subject, an affective information category whose factors are sensory characteristics related to the lips or body of the subject, and a color information category whose factors are color information related to the lips or body of the subject, and by using as output factors a factor different from the input factors, the lip evaluation system comprising: a 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; an input means for inputting the plurality of input factors obtained from the subject; and a calculation means for calculating the output factor based on the mathematical model and the input factors. [Effects of the Invention]

[0008] According to the method provided by the present invention, it is possible to perform lip evaluation using information belonging to the physiological information category, and therefore lip evaluation can be performed using multifaceted information. [Brief explanation of the drawings]

[0009] [Figure 1](a) A diagram showing the chromatic characteristics of people with pink lip colors, (b) A diagram showing the chromatic characteristics of people with pale lip colors, (c) A diagram showing the chromatic characteristics of people with purple lip colors, and (d) A diagram showing the chromatic characteristics of people with brown lip colors. [Figure 2] (a) is a diagram showing the distribution of lip L* (lightness) by lip color type, (b) is a diagram showing the distribution of lip C* (saturation) by lip color type, and (c) is a diagram showing the distribution of lip h (hue) by lip color type. [Figure 3] FIG. 10 is a diagram showing the percentage of subjects by lip color type by age group. [Figure 4] FIG. 1 is a diagram showing the relationship between lip color type and melanin index. [Figure 5] FIG. 1 is a diagram showing lip color types and ATI (peak blood flow position). [Figure 6] FIG. 10 is a diagram showing an example of an MBR time waveform. [Figure 7] FIG. 2 is a diagram showing each part of the lips. [Figure 8] FIG. 10 is a diagram showing the correlation between lip color and somatovisual category. [Figure 9] 1 is a flowchart illustrating a lip evaluation method. [Figure 10] FIG. 10 is a diagram showing an overview of implementation pattern 1. [Figure 11] FIG. 10 is a diagram showing an overview of implementation pattern 2. [Figure 12] FIG. 10 is a diagram showing an overview of implementation pattern 3. [Figure 13] FIG. 10 is a diagram showing an overview of implementation pattern 4. [Figure 14] FIG. 10 is a diagram showing an overview of implementation pattern 5. [Figure 15] FIG. 10 is a diagram showing an overview of implementation pattern 6. [Figure 16] FIG. 1 is a conceptual diagram of a lip information evaluation system. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. Note that the drawings of the present embodiments are intended to explain the technical concept, configuration, and operation of the present invention, and are not intended to specifically limit the configuration. In addition, in all drawings, similar components are designated by similar reference numerals, and duplicated descriptions will be omitted as appropriate.

[0011] <Summary> An outline of the lip evaluation method according to this embodiment will be described. The lip evaluation method of this embodiment (hereinafter may be referred to as this method) is a method for evaluating the lip or body characteristics of a subject using a plurality of factors as input factors, including one or more factors belonging to a physiological information category, from a category group consisting of a physiological information category whose factors are physiological characteristics related to the lips or body of the subject, an affective information category whose factors are sensory characteristics related to the lips or body of the subject, and a color information category whose factors are color information related to the lips or body of the subject, and a factor different from the input factors, to evaluate the lip or body characteristics of the subject, using a mathematical model obtained in advance from a population and showing the correlation between the plurality of input factors and the output factor, and the plurality of input factors obtained from the subject.

[0012] Until now, lip color classification has been based solely on differences in lip color information, such as brightness, saturation, and hue, as in Patent Document 1, for example. However, differences in lip color are influenced by physiological information, such as the type and amount of pigment contained in the lips, differences due to characteristics of lip blood flow, and lip shape, as well as physiological characteristics of the lips, such as the subject's age. The present inventors have discovered 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 lips using information belonging to a physiological information category, which factors in physiological characteristics related to the subject's lips or body.

[0013] This lip evaluation method uses a plurality of factors, including one or more factors belonging to the physiological information category, among the many factors belonging to the physiological information category, the many factors belonging to the sensory information category, and the many factors belonging to the color information category, to evaluate the lips. To facilitate understanding of the present invention, among the color group factors divided using lip pigment information, color group A factors (factors belonging to the color type category) and factors belonging to the color information category (L * (lightness), C * We will first provide a specific explanation of the correlation between color and the color components (color saturation, h (hue)), and then explain each factor and each category.

[0014] Figure 1 shows the results of lip color classification, based on lip color (mainly the lower lip) assessment of 85 Japanese female subjects in their 20s to 70s. Evaluation was performed visually by three expert evaluators familiar with lip color. First, lip colors with similar colors were assessed to minimize the number of types (first assessment). A reassessment was then performed using the same photographs after a set number of days (second assessment), and the final color classification was determined. If the results of the first and second assessments differed, a reassessment was performed. As a result of the assessment, as shown in Figure 1, the lip colors of Japanese women can be classified into four types. In this specification, each type is given a tentative color name and will be described as (a) pink type, (b) pale type, (c) purple type, and (d) brown type. However, there is no clear boundary, and it is common for multiple types to be combined, such as a pink type and a pale type. Here, the absence of a clear boundary refers to the fact that the color information (L) of the four groups is inconsistent. * , C * , h, etc.) have different central values, but are not completely separated without overlapping, meaning that there are areas that overlap partially. Here, the characteristics of each type will be described.

[0015] Figure 1(a) Pink type has bright red lips. * is high, C * is high and h is low. Figure 1(b) Pale type is a lip color without redness. * is high, C * is low and h is high. Figure 1(c) Purple type is a lip color with low saturation. * is high, C * is low and h (hue) is low. Figure 1(d) Brown type has dark lip color. * is low, C * is low and h is high.

[0016] Figures 2(a) to (c) show the L * , C * , and h, and what color types are distributed at what values. Figure 2(a) shows the L of the subjects' lips by color type. * The horizontal axis represents color type, and the vertical axis represents L * As is clear from Figure 2(a), the pink, pale, and purple types have different L * There is no significant difference in the values ​​of L * There is no significant difference between the pink, pale, and purple types, but there is a significant difference between the purple and brown types, and there are also significant differences between the pink and brown types, and between the pale and brown types. Figure 2(b) shows the C of the subjects' lips by color type. * The horizontal axis represents the color type, and the vertical axis represents the saturation value. As is clear from Figure 2(b), the pink type is distributed in the C * The pale, purple and brown types are distributed in high values, but the C * The pink type is significantly different from each of the other types, and there are also significant differences between the pale type and the purple type, and between the purple type and the brown type. Figure 2(c) shows the distribution of h for the subjects' lips by color type. The horizontal axis represents color type, and the vertical axis represents h. The redder the lip color, the lower the h value. As is clear from Figure 2(c), the pink and purple types have low h values, while the pale and brown types have high h values. There are significant differences between the pink and pale types, and between the pink and brown types.

[0017] Figure 3 shows the distribution of color types among subjects by age group. The horizontal axis shows age, and the vertical axis shows the proportion of subjects with each color type. For example, the proportion of pink types is high among people in their 20s, and the proportion of purple types is high among people in their 70s. Furthermore, the proportion of pink types decreases as the age group increases. In this way, the proportion of subjects with each color type varies depending on age group.

[0018] Figure 4 shows the distribution of melanin index (MI) of the subjects' lips by color type. The horizontal axis represents color type, and the vertical axis represents MI. Of the four types, the pink, pale, and purple types have low MI values, while the brown type has high MI values. There are significant differences between the brown type and the pink, pale, and purple types.

[0019] Figure 5 shows the ATI (peak blood flow position) by color type. The lower the ATI, the earlier the peak is reached. The pink type has blood flow that reaches its peak quickly, while the pale and purple types have slower peaks. Table 1 summarizes the details of Figures 1 to 5.

[0020] [Table 1]

[0021] As shown in Table 1, the factors belonging to the color information category (L * , C *, h) and factors (MI, ATI) belonging to the physiological information category, and the features estimated therefrom, by classifying lip color into types, it becomes possible to make suggestions based on the classification results, taking into account physiological information factors that are factors in lip color information, when proposing makeup methods, makeup products, care methods, care products, etc. For this reason, in this method, lip evaluation is performed using, for example, information belonging to the physiological information category, which is based on the physiological characteristics of the subject's lips or the subject's age.

[0022] Next, each factor used in this lip evaluation method and each category to which each factor belongs will be described. Table 2 shows the categories of each factor in this embodiment.

[0023] [Table 2]

[0024] As shown in Table 2, in this embodiment, the categories are comprised of a "physiological information category" based on physiological characteristics of the subject's lips or body as factors, a "sensory information category" based on sensory characteristics of the subject's lips or body as factors, and a "color information category" based on color information of the subject's lips or body as factors. The "physiological information category," "sensory information category," and "color information category" each include lip-related factors and factors other than lip-related factors. In this embodiment, the major categories are the "physiological information category," the "sensory information category," and the "color information category." The intermediate categories are 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," and the "gender category" that belong to the "physiological information category," the "lip visual category," the "lip tactile category," the "lip somatosensory category," the "body visual category," the "body tactile category," and the "body somatosensory category," and the "lip color category" and the "body color category" that belong to the "color information category." Furthermore, as will be described in detail later, factors belonging to the intermediate classification category may be composed of a single element, such as the measurement value itself, or may be composed of multiple elements, such as a numerical range (for example, for age, a range such as teens, twenties, etc.) or a perceived level (for example, for complexion, very applicable / applicable / not applicable). When composed of multiple elements, there are those composed of multiple elements where the numerical range set for each factor indicates the degree of the factor, those composed of multiple elements where each set level indicates the degree of the factor, such as very applicable / applicable / not applicable, and, for example, in the case of each factor belonging to the color type category, those composed of elements determined by visual evaluation (those composed of multiple elements that classify the factor).

[0025] The "physiological information category" is a category to which factors of the physiological characteristics of the subject's lips and the subject's body belong. In this embodiment, categories are further defined for each physiological characteristic factor. The categories include a "pigment category" using lip pigment information as a factor, a "blood flow category" using lip blood flow information as a factor, a "blood vessel category" using lip blood vessel information as a factor, a "shape category" using lip shape information as a factor, a "surface shape index category" using lip surface shape index information as a factor, a "color type category" using lip color group information as a factor, a "body category" using the physiological characteristics of the subject's body as a factor, an "age category" using the subject's age information as a factor, and a "gender category" using the subject's gender information as a factor.

[0026] The "pigment category" includes factors that are indicators (pigment information) related to the type and amount of pigment in the lips. The apparent color of the lips changes depending on the type and amount of pigment, so the factors in the lip color category (L * However, since the amount of pigment is a physiological characteristic, the pigment category belongs to the "physiological information category." In this embodiment, MI (melanin index) and EI (erism 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 hemoglobin content. For example, at low MI, 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.

[0027] The "blood flow category" includes MBR (Mean Blur Rate): blood flow rate, Fluctuation: rate of change in blood flow rate, Skew: bias of blood flow waveform, BOS (Blowout Score): steady blood flow, BOT (Blowout Time): sustained high blood flow, Rising rate: time variation in the rate of blood flow increase, Falling rate: time variation in the rate of blood flow decrease, FAI: maximum acceleration of blood flow increase, ATI: position of peak blood flow, and RI (Resistivity Index): peripheral vascular resistance. Each factor in the blood flow category is composed of not only the measured value itself but also a numerical range set for each factor, and each range is used as an element.

[0028] MBR is the relative blood flow rate, and is a value obtained by applying the average MBR value to the linear regression equation: blood flow rate mL / (min·100 g)=41.7×MBR value−15.1. Fluctuation is an index that indicates the coefficient of variation of MBR. Skew is a value that indicates the deviation of the blood flow waveform. BOS is a value that indicates steady state blood flow. BOT is an index showing the sustainability of a high MBR value, and the BOT value is expressed by the following equation using the half-width (time) (W) and one-beat width (time) (F) of the MBR value shown in Figure 6, and a proportionality constant "C". (BOT)=C·(W) / (F) Rising rate is an index that indicates the time variation of the rate of blood flow increase. The falling rate is an index that indicates the time variation of the rate of decline from the maximum MBR value in the time waveform of the MBR value per heartbeat. Using (Sall) and (S2) shown in Figure 6, the falling rate can be expressed by the following equation. In the following, "C" is a proportionality constant. (Falling rate)=C·(S2) / (Sall) FAI indicates the instantaneous maximum blood flow rate when blood flow increases. The ATI is the proportion of the time during which the MBR time waveform reaches the maximum MBR value (MBRmax in FIG. 6) 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.

[0029] The "vascular category" includes information about the blood vessels of the lips, such as area, width, length, density, and branching. Each factor of area, width, length, density, and branching is composed of not only the measured value itself measured from image data of the lips, but also a numerical range set for each factor, and each range is configured as an element.

[0030] The "shape category" includes the width of the velum of the upper lip, the length of the velum of the upper lip, the fullness of the vermilion of the lower lip, and the vertical and horizontal widths of the vermilion. Figure 7 shows the length, width, and other parts of each factor in the shape category. Factors in the shape category are configured by setting a numerical range for each factor in addition to the actual values ​​of each part shown in Figure 7, and each range is used as an element. Also, although not shown in Table 2, types such as thin lip type, thick lip type, type with only a thick upper lip, or type with only a thick lower lip are also possible.

[0031] The "surface shape index category" includes wrinkle-derived and peel-derived factors. Wrinkle-derived factors are values ​​obtained from the depth, length, width, etc., obtained from surface irregularity information. Peel-derived factors are values ​​obtained from the unevenness of minute irregularities on the surface. Factors that belong to the surface shape index category are configured by setting a numerical range for each factor in addition to the obtained value itself, and each range is used as an element.

[0032] The "color type category" includes the color group A, which is composed of the above-mentioned "pink type" element, "pale type" element, "purple type" element, and "brown type" element, as well as the color pink group, which is composed of dark pink type element and light pink type element. In this embodiment, the elements that compose each color group, which is each factor, are determined by, for example, measuring the lip color of the measured L that belongs to the lip color category. * , a * (The larger the positive value, the redder the color, and the larger the negative value, the greener the color. The larger the absolute value, the more vivid the color.) *(The larger the positive value, the more yellow the color, and the larger the negative value, the more blue the color. The larger the absolute value, the more vivid the color becomes.) * This is done by cluster classification using the values ​​of h and Age, which belongs to the age category. As mentioned above, the lip color becomes less red and more brown with age, so L * , a * , b * , C * It is preferable to determine the color type by taking into consideration not only factors belonging to the lip color category such as , h, but also factors belonging to the age category (Age). In this way, factors of the age category included in the physiological information category are used to determine the elements of each color group in the color type category, so in this embodiment, the "color type category" is included in the physiological information category. Note that factors of the age category are not used to determine the elements of each color group, and only the color appearance (factors of the lip color category (L)) is used. * If only lip color (e.g., lip gloss) is used, Color Group A may be included in the lip color category.

[0033] "Physical category" is a category to which factors related to physical information such as height, weight, BMI (Body Mass Index), blood pressure, heart rate, etc. In addition to the obtained values ​​themselves, a numerical range is set for each factor, and each range is configured as an element. "Age category" refers to age itself or a generation (such as 20s, 30s, etc.), and when generation is a factor, for example, 20s, 30s, 40s, etc. are the elements that make up the generation." The "gender category" is a factor of gender, and elements constituting gender may include not only male and female, but also elements such as masculine and feminine.

[0034] The "sensory information category" is a category to which sensory feature factors related to the subject's lips and the subject's body belong. In this embodiment, the sensory feature factors are further divided into categories for each feature. There are provided a "lip visual category" that uses visual information for the lips as a factor, a "lip tactile category" that uses tactile information for the lips as a factor, a "lip somatosensory category" that uses somatosensory information for the lips as a factor, a "body visual category" that uses visual information for the body, particularly the face, neck, and décolleté close to the lips, as a factor, a "body tactile category" that uses tactile information for the body, particularly the face, neck, and décolleté close to the lips, as a factor, and a "body somatosensory category" that uses somatosensory information for the body, particularly the face, neck, and décolleté close to the lips, as a factor.

[0035] Here, the results of an experiment conducted on the influence of lip color on body impression (facial impression) will be described. <Experimental Method> 31 people Evaluators (8 in their 20s, 10 in their 30s, 6 in their 40s, 7 in their 50s: 17 men, 14 women) Method: Stimulus pairs created from average faces 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) Attractiveness rated on a 5-point scale Stimulus: The average face of a person in their 40s (original image) with only the lip color removed. * , a * , b * Seven stimulus images, each varied by ±5 based on the color system. Note that the facial colors in images A to G are all the same, with only the lip color varied. Figure 8 shows the experimental results.

[0036] From Figure 8, for example, the L of the lips * Increasing the value makes the face appear "brighter" and the L of the lips * If the value is reduced, the complexion does not appear brighter, and the L of the lips * It can be said that there is a relationship between the value of and whether the face is perceived as bright or not. * Increasing the value makes the face appear "brighter" and the lips appear more* If the value is reduced, the complexion does not appear brighter, and the a * It can be said that there is a relationship between the value and whether or not one's complexion appears bright. Similarly, for example, the lip L * When the value is reduced, it is clear that the complexion does not "feel good" and the L of the lips * It can be said that there is a relationship between the value and whether the complexion feels good or not. * Higher values ​​make the complexion "feel" better, and the lip a * When the value is reduced, it is clear that the complexion is "not good" and the lip a * It can be said that there is a relationship between the value and whether or not one's complexion looks good. Similarly, for example, the lip L * It is clear that the skin does not "feel beautiful" when the value is reduced, and the L * It can be said that there is a relationship between the value and whether the skin feels beautiful or not. * Higher values ​​make the skin look "cleaner" and the lips look * It is clear that the skin does not "feel beautiful" when the value is reduced, and the a * It can be said that there is a relationship between the value and whether or not your skin feels beautiful. Similarly, for example, the lip L * It is clear that a smaller value makes the subject appear less attractive, and the L * Similarly, for example, the a of the lips * A higher value makes the lips appear more attractive, * It is clear that a smaller value makes the subject less attractive, and the lips * It can be said that there is a relationship between value and whether or not something is perceived as attractive. In this way, it is clear that there is a relationship between lip color (lip color category) and body visual perception category, and it is also clear that the visual perception of the face changes just by changing the lip color without changing the facial color.

[0037] The "lip visual impression category" includes factors such as complexion, transparency, bright color, good color, beautiful, and attractive. Complexion refers to how the subject or other subjects feel about the complexion when looking at the lips, and is composed of, for example, elements such as "the complexion looks good (applies)" or "doesn't look good (doesn't look good (doesn't look good)"). Transparency refers to how the subject or other subjects feel about the transparency when looking at the lips, and is composed of, for example, elements such as "the complexion looks clear (applies)" or "doesn't look clear (doesn't look good ... Beauty refers to how the subject or another subject feels about beauty when looking at the lips, and is composed of, for example, elements of "looks beautiful" / "doesn't look beautiful (doesn't apply)." Attractiveness refers to how the subject or another subject feels about attractiveness when looking at the lips, and is composed of, for example, elements of "looks attractive" (does apply) / "doesn't look attractive (doesn't apply). In this embodiment, all factors included in the visual category are composed of two elements, "applies" / "doesn't apply," but this is not a limitation, and all factors may be composed of three elements, "very applicable," "applies," and "doesn't apply." Furthermore, some factors may be composed of two elements and other factors may be composed of three elements.

[0038] The "lip texture category" includes factors such as roughness and elasticity. Roughness is comprised of the elements of whether the subject or another subject felt it was rough when touching their lips (applies) / did not feel it was rough (does not apply). Elasticity is comprised of the elements of whether the subject or another subject felt it was elastic when touching their lips (applies) / did not feel it was elastic (does not apply). In this embodiment, all factors included in the texture category are comprised of two elements, "applies" / "does not apply," but this is not a limitation, and all factors may be comprised of three elements, "very applicable," "applies," and "does not apply." Furthermore, some factors may be comprised of two elements and other factors of three elements.

[0039] The "lip somatic sensation category" includes factors such as a feeling of tightness and a feeling of dryness. The feeling of tightness is comprised of the elements of whether the subject felt that their lips were tight (applies) or not (does not apply). The feeling of dryness is comprised of the elements of whether the subject felt that their lips were dry (applies) or not (does not apply). In this embodiment, all factors included in the somatic sensation category are comprised of two elements, "applies" or "does not apply," but this is not limited to this, and all factors may be comprised of three elements, "very applicable," "applies," and "does not apply." Furthermore, some factors may be comprised of two elements and other factors of three elements.

[0040] The "body visual perception category" includes factors such as complexion, transparency, bright color, good color, beautiful, and attractive. Complexion refers to how the subject or other subjects perceive the complexion when looking at the body, and is composed of, for example, elements such as "the complexion looks good (applies)" or "the complexion looks bad (does not apply)." Transparency refers to how the subject or other subjects perceive the transparency when looking at the body, and is composed of, for example, elements such as "the complexion looks transparent (applies)" or "it does not look transparent (does not apply)." Bright color refers to how the subject or other subjects perceive the brightness of the color when looking at the body, and is composed of, for example, elements such as "the color looks bright (applies)" or "it does not look bright." Good color refers to how the subject or other subjects perceive the good color when looking at the body, and is composed of, for example, elements such as "the color looks good (applies)" or "it does not look good (does not apply)." Beauty is how the subject or another subject feels about beauty when looking at the lips, and is composed of, for example, elements such as "looks beautiful" / "doesn't look beautiful" (doesn't apply). Attractiveness is how the subject or another subject feels about attractiveness when looking at the body, and is composed of, for example, elements such as "looks attractive" (does apply) / "doesn't look attractive" (doesn't apply). In this embodiment, all factors included in the body visual perception category are composed of two elements, "applies" / "doesn't apply," but this is not a limitation, and all factors may be composed of three elements, "very applicable," "applies," and "doesn't apply." Furthermore, some factors may be composed of two elements and other factors may be composed of three elements.

[0041] The "body texture category" includes factors such as roughness and elasticity. Roughness is comprised of the elements of whether the subject or another subject felt it was rough when touching the body (applies) / whether it was not rough (does not apply). Elasticity is comprised of the elements of whether the subject or another subject felt it was elastic when touching the body (applies) / whether it was not elastic (does not apply). In this embodiment, all factors in the body texture category are comprised of two elements, "applies" / "does not apply," but this is not a limitation; all factors may be comprised of three elements, "very applicable," "applies," and "does not apply." Furthermore, some factors may be comprised of two elements and other factors of three elements.

[0042] The "body somatic sensation category" includes factors such as a feeling of tightness and a feeling of dryness. The feeling of tightness is comprised of the elements of whether the subject felt that their body was tight (applies) or not (does not apply). The feeling of dryness is comprised of the elements of whether the subject felt that their body was dry (applies) or not (does not apply). In this embodiment, all factors included in the body somatic sensation category are comprised of two elements, apply / do not apply, but this is not limited to this, and all factors may be comprised of three elements, very applicable, apply, and do not apply. Furthermore, some factors may be comprised of two elements and other factors of three elements.

[0043] The "color information category" is a category to which the colorimetric values ​​of the subject's lips and body or information factors for identifying the type of color based on the colorimetric values ​​belong, and further categories are established for each part of the subject, such as a "lip color category" in which color information related to the lips is a factor, and a "body color category" in which color information related to the body, particularly the face, neck, and décolleté close to the lips, is a factor.

[0044] The lip color category is a category to which factors of information for identifying the color type based on the color measurement values ​​of the lips or the color measurement values ​​belong. In this embodiment, the following factors belong to the lip color category. L* is the brightness. a * The larger the positive value, the more red the color tends to be, and the larger the negative value, the more green the color tends to be. The larger the absolute value, the more vivid the color becomes. b * The larger the positive value, the more yellow the color tends to be, and the larger the negative value, the more blue the color tends to be. The larger the absolute value, the more vivid the color becomes. C * is the saturation. h is the hue. R is a value related to the intensity of long wavelengths (red region) in RGB, a type of color expression. G is a value related to the intensity of the medium wavelength (green region) in RGB, which is a type of color expression. B is a value related to the intensity of short wavelengths (blue region) in RGB, a type of color expression. The optical spectrum expresses the relative proportion of each single color. A color swatch is a list of color samples created according to a predetermined standard. The color difference is a value that represents the difference in color, for example, a value that represents the difference between the red lip portion and the white lip portion. Color unevenness indicates the spatial non-uniformity of color, and is a value obtained from frequency, histogram shape (variance, skewness, kurtosis, etc.), statistics, etc.

[0045] The body color category is a category to which factors of information for identifying the color type based on the measured color values ​​of the body or the measured color values ​​belong. In this embodiment, the factors belonging to the body color category are similar to those in the lip color category, and therefore a description thereof will be omitted.

[0046] The factors listed in Table 2 are those in this embodiment, and other factors may be included.

[0047] This method will now be described. A "physiological information category with factors being physiological characteristics of the subject's lips or body" is a category to which factors of the physiological characteristics of the subject's lips and body belong, and 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, a "shape category" with lip shape information as a factor, a "surface shape index category" with lip surface shape index information as a factor, a "color type category" with lip color group information as a factor, a "body category" with factors being physiological characteristics of the subject's body, an "age category" with subject age information as a factor, or a "gender category" with subject gender information as a factor. A "sensory information category with sensory characteristics related to the subject's lips or body as factors" is a category to which factors of sensory characteristics related to the subject's lips and body belong, and includes a "lip visual category" with visual information for the lips as a factor, a "lip tactile category" with tactile information for the lips as a factor, a "lip somatosensory category" with somatosensory information for the lips as a factor, a "body visual category" with visual information for the body, particularly the face, neck, and décolleté close to the lips as a factor, a "body tactile category" with tactile information for the body, particularly the face, neck, and décolleté close to the lips as a factor, and a "body somatosensory category" with somatosensory information for the body, particularly the face, neck, and décolleté close to the lips as a factor. A "color information category that uses color information about the subject's lips or body as a factor" is a category to which factors of information for identifying the type of color based on colorimetric values ​​or colorimetric values ​​of the subject's lips and body belong, and includes a "lip color category" that uses color information about the lips as a factor and a "body color category" that uses color information about the body, particularly the face, neck, and décolleté that are close to the lips, as factors. The "category group" is composed of the "pigment category," "blood flow category," "blood vessel category," "shape category," "surface shape index category," "color type category," "body category," "age category," and "gender category" in the physiological information category; the "lip visual category," "lip tactile category," "lip somatosensory category," "body visual category," "body tactile category," and "body somatosensory category" in the sensory information category; and the "lip color category" and "body color category" in the color information category. "Multiple factors from the category group, including one or more factors belonging to the physiological information category, are used as input factors" means that one or more factors belonging to the physiological information category and factors belonging to other categories may be used as input factors, or two or more factors belonging to the physiological information category may be used as input factors, or all of the multiple factors may belong to the physiological information category. "Evaluating the lip or body features of a subject using factors different from the input factors as output factors" means that, as long as factors different from the input factors are output as output factors, the category to which the input factors belong and the category to which the output factors belong may be the same or different. Also, it means evaluating the lip or body features of the subject, such as external aspects such as color and appearance, or internal aspects such as blood flow, according to the calculated output factors. A "mathematical model that shows the correlation between multiple input factors and output factors obtained in advance from a population" is a mathematical model that shows the relationship between multiple input factors and output factors, created from information about each factor obtained in advance from a population consisting of multiple subjects. Mathematical models that output a single element or the value of a single element include threshold judgment based on summary statistics (location, variance, moment) from the population, multiple regression analysis, K-nearest neighbor method, logistic regression, and regression tree. Mathematical models that output multiple elements or the ratio of multiple elements include naive Bayes classifiers, gradient boosting, support vector machines, neural networks, and deep learning. "Determining the output factors based on the plurality of input factors obtained from the subject" means determining the output factors based on the input factors and a mathematical model.

[0048] Next, an overview of the processing flow of this method will be described using FIG. 9 . Details will be described later. FIG. 9 shows a processing flow for determining both the value of one element or elements of a corresponding output factor and the ratio of multiple elements and multiple elements of the corresponding output factor. However, only one of these may be determined. In this embodiment, determining the value of one element or elements of a corresponding output factor is sometimes referred to as "deterministically determining," and determining the ratio of multiple elements and multiple elements of the corresponding output factor is sometimes referred to as "determining as a ratio." FIG. 9 also illustrates the use of a predetermined mathematical model to calculate the value of one element or elements, and the use of a predetermined mathematical model to calculate multiple elements and multiple ratios of multiple elements. In this embodiment, calculating the value of one element or elements using a predetermined mathematical model is sometimes referred to as "calculating in simple mode," and calculating multiple elements and multiple ratios of multiple elements is sometimes referred to as "calculating in careful mode."

[0049] The step (step S100) is a step of determining input factors and output factors. In this method, multiple factors including factors included in the lip physiological information category are used as input factors, and factors different from the input factors can be output. Therefore, input factors and output factors are determined, and output factors are obtained based on the determined input factors. Any combination and type of input factors and output factors may be determined, but the accuracy of the obtained output factors varies depending on the input factors. Therefore, it is preferable that by determining the output factors to be obtained, a combination and type of input factors with high accuracy are automatically determined or recommended as factors.

[0050] In step S110, it is determined whether to calculate an output factor for one element or the value of one element, or to calculate multiple elements and a ratio of multiple elements as output factors; in other words, whether to calculate in simple mode or careful mode. This step may be automatically determined depending on the output factor to be calculated. If an output factor for one element or the value of one element is to be calculated, proceed to step S120. If multiple elements and a ratio of multiple elements are to be calculated as output factors, proceed to step S130.

[0051] In step S120, when it is decided to calculate the output factors in the simple mode in step S110, the output factors are calculated using the input factors determined in step S100 and a mathematical model for calculating the output factors of one element or the value of one element. The mathematical model shows the relationship between the input factors and the output factors from the population.

[0052] In step S130, when it is determined in step S110 that the output factors are to be calculated in the careful mode, the output factors are calculated using the input factors determined in step S100 and a mathematical model that calculates multiple elements and their ratios. The mathematical model shows the relationship between the input factors and the output factors from the population.

[0053] The step (step S140) is a step of determining whether to use the multiple elements and the ratios of the multiple elements determined in step S130 as they are to propose, for example, a recommended skin care method or makeup method, or to identify an output factor for one element based on the determined multiple elements and the ratios of the multiple elements and use the identified output factor to propose a recommended skin care method or makeup method. This step may be determined automatically depending on the output factor to be determined. It is also preferable to determine which output factor to use depending on how the output factor is to be used (such as proposing a skin care method or makeup products).

[0054] Step (Step S150) is a step of identifying an output factor of one element when it is determined in Step S140 that an output factor of one element is to be identified. The method of identification corresponds to identifying the output element with the highest / lowest ratio, or having a staff member or a user at a store identify the output factor.

[0055] The step (step S160) is a step of suggesting a skin care method, a makeup product, etc. based on the output factors determined in step S120, step S130, or step S150. Note that this step is a step that utilizes the output factors determined by this method, and is therefore not included in this method. Also, steps S110 and S140 may be automatically determined by determining the input factors and output factors in step S100, and therefore may not be included in this method. Furthermore, this method may be either a simple mode or a thorough mode.

[0056] Next, lip evaluation performed using this method will be described. Note that the following implementation patterns are merely examples. Implementation patterns 1 to 3 are examples of a thorough mode in which a Gaussian-Naive Bayes model is used as a mathematical model showing the correlation between multiple input factors and output factors, and multiple elements and the ratio of multiple elements are calculated as output factors. 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 multiple input factors and output factors, and an output factor for one element or the value of one element is calculated. Each mathematical model was created in advance using the measured values ​​of the factors listed in Table 2 for the population of 85 people described in Figure 1. Furthermore, when factors in the color information category are used as input factors, the measured values ​​of the user's bare lips are used. This allows for accurate evaluation of the user's lips. Furthermore, when a color group (color type) is used as an input factor, the color type can be calculated in advance from the measured values ​​of factors in the color information category and the measured values ​​of factors included in the physiological information category. Furthermore, factors belonging to the shape category may be obtained by acquiring an image of the user's lips in advance and measuring the size of each part of the lip image.

[0057] <Implementation pattern 1> Figure 10 shows an overview of implementation pattern 1. In the implementation pattern 1, based on the Gaussian Naive Bayes model created using the measurement values ​​of the population (85 people in this embodiment), the ratio of the likelihood of each of the elements belonging to color group A of the color type category: pink type, pale type, purple type, and brown type was calculated. * The input factors were the user's measurements (three variables) of h and MI belonging to the pigment category of the physiological information category. That is, the factors belonging to the pigment category of the physiological information category (e.g., MI) and the factors belonging to the lip color category of the color information category (e.g., C * , and h) were used as input factors, and factors belonging to the color type category included in the physiological information category (e.g., color group A: pink type, pale type, purple type, and brown type) were obtained as output factors. As shown in Figure 10, the generalization performance of this model for the test data was high, with a correct answer rate of 0.88 (88%). In addition, the classification evaluation performed with this model also showed the highest rate of classification into the desired factor. Then, the user's measurement value (C *Using the output factors (H:20, h:40, MI:45) and a mathematical model, the output factors were found to be such that the ratios of multiple elements belonging to color group A were most likely to belong to the pink type, brown type, pale type, and purple type, in that order. Using these results, for example, when recommending recommended makeup products (lipstick), it is possible to suggest not only makeup products suitable for pink-type users, but also makeup products suitable for brown-type users. By making such suggestions, even if a user prefers makeup products suitable for brown-type users (favorite colors) over makeup products suitable for pink-type users, the user will be able to more easily select makeup products suitable for brown-type users, making it possible to make appropriate suggestions. Furthermore, in the case of implementation pattern 1, the user's color type is least likely to be purple, so it is also possible to suggest that it would be better not to select makeup products suitable for purple-type users. As mentioned above, there is no clear boundary between lip color types, so by finding the most likely color type, as in Implementation Pattern 1, it is possible to make suggestions that are appropriate for lip color types that do not have clear boundaries, compared to, for example, finding only one specific color type and suggesting makeup products and care methods that correspond to that color type. In this way, using a mathematical model, multiple elements of factors that belong to one of the categories based on the input factors (in the case of implementation pattern 1, multiple elements that belong to color group A of the color type category) are classified according to the proportions to which they each apply and output.

[0058] <Implementation pattern 2> Figure 11 shows an overview of implementation pattern 2. In the second implementation, based on the Gaussian Naive Bayes model created using the measurements of the population (85 people in this embodiment), the ratio of the likelihood of each of the elements belonging to color group A in the color type category: pink type, pale type, purple type, brown type was calculated. * , a * , b *, C * The input factors were the user's measurements (eight variables) of h, Age belonging to the age category of the physiological information category, and MI and EI belonging to the pigment category. That is, factors belonging to the physiological information category (e.g., Age, MI, and EI) and factors belonging to the lip color category of the color information category (e.g., L * , a * , b * , C * , and h) were used as input factors, and factors belonging to the color type category included in the physiological information category (e.g., color group A: pink type, pale type, purple type, and brown type) were obtained as output factors. As shown in Figure 11, the generalization performance of this model for the test data was high, with a correct answer rate of 0.76 (76%). In addition, the classification evaluation performed with this model also showed the highest rate of classification into the desired factor. And this input factor (L * :43, a * :14, b * :15, C *Using the mathematical model (e.g., :20, h:40, Age:20, MI:45, EI:73), the output factors were calculated. The results showed that the ratios of multiple elements belonging to color group A were most likely to belong to pale type, pink type, brown type, and purple type, in that order. Using these results, for example, when recommending recommended makeup products (lipstick), it is possible to suggest not only makeup products suitable for pale type users, but also makeup products suitable for pink type users. By making such suggestions, even if a user prefers makeup products suitable for pink type users (favorite colors) over makeup products suitable for pale type users, the user can more easily select makeup products suitable for pink type users, making it possible to make appropriate suggestions. Furthermore, in the case of implementation pattern 2, since it is highly unlikely that the user's color type is purple, it is also possible to suggest that it would be better not to select makeup products suitable for purple type users. As mentioned above, there is no clear boundary between lip color types, so by finding the most likely color type, as in Implementation Pattern 2, it is possible to make suggestions that are appropriate for lip color types that do not have clear boundaries, compared to, for example, finding only one specific color type and suggesting makeup products and care methods that correspond to that color type. In this way, using a mathematical model, multiple elements that belong to one of the categories based on the input factors (in the case of implementation pattern 2, multiple elements that belong to color group A of the color type category) are classified according to the proportions to which they each belong and output.

[0059] <Implementation pattern 3> FIG. 12 shows an overview of implementation pattern 3. In implementation pattern 3, based on a Gaussian Naive Bayes model created using measurements from the population (85 people in this embodiment), the ratio of the likelihood of each of the age groups in the physiological information category belonging to the age categories: 20s, 30s, 40s, 50s, 60s, and 70s was calculated. Implementation pattern 3 is L, which belongs to the lip color category of the color information category. * , and C* The input factors were the user's measurements (8 variables) of MBR, Skew, ATI, RI, which belong to the blood flow category of the physiological information category, and MI and EI, which belong to the pigment category. As shown in Figure 12, the generalization performance of this model for the test data was 0.47 (47%). In addition, the evaluation of classification performed by this model showed that the percentage of classifications into the desired elements was the highest. And these input factors (L * :44.824, and C * Using the mathematical model (Figure 1), the output factors were calculated, revealing a significantly higher ratio for users in their 40s and a lower ratio for users in their 30s and 20s. Since the user's actual age is 42, this result is considered highly accurate as an output factor element value. Using this result, for example, when recommending makeup products (lipstick), it is possible to suggest not only makeup products suitable for users in their 40s, but also makeup products suitable for users in their 30s and 20s. By making such suggestions, even if a user prefers makeup products (preferred colors) for users in their 30s and 20s over makeup products suitable for users in their 40s, the user will be able to more easily select makeup products suitable for users in their 30s and 20s, thereby enabling more appropriate suggestions. In addition, in the case of implementation pattern 3, since the user's age group is unlikely to be in their 50s, 60s, or 70s, it is possible to suggest that it would be better not to select makeup products suitable for people in their 50s, 60s, and 70s. In this way, using a mathematical model, multiple factors that belong to a category based on the input factors (in the case of implementation pattern 3, multiple elements that belong to the age category) are classified and output according to the proportions to which each corresponds.

[0060] <Implementation pattern 4> FIG. 13 shows an overview of implementation pattern 4. In the fourth embodiment, the ages belonging to the age categories of the physiological information category were calculated based on a multiple regression equation created using measurements from a population (85 people in this embodiment). The input factors in the multiple regression equation were selected based on domain knowledge. Implementation pattern 4 is L, which belongs to the lip color category of the color information category. * , and C * The input factors were factors included in the color type category of the physiological information category (e.g., color group A: pink type, pale type, purple type, and brown type), and multiple factors (L * , C * , and h) were used as input factors, and factors included in the age category, which is a category different from the category to which the input factors belong (for example, Age is equivalent), were obtained as output factors. As shown in Figure 13, the coefficient of determination (R 2 ) was 0.64, clearly showing a strong correlation. Therefore, by inputting the user's measured values ​​corresponding to the above input factors into the explanatory variables of the multiple regression equation shown in Figure 13, it is possible to determine the user's age with high accuracy. In addition, the factors included in the age category output in Implementation Pattern 4 are limited to age information.

[0061] <Implementation pattern 5> FIG. 14 shows an overview of implementation pattern 5. In the fifth embodiment, the MI (melanin index) belonging to the pigment category of the physiological information category was calculated based on a multiple regression equation created using the measurements of the population (85 people in this embodiment). The variables in the multiple regression equation were selected using domain knowledge. Implementation pattern 5 is L, which belongs to the lip color category of the color information category. * , C *The input factors were the user's measurements (four variables) of h and Age, which belong to the age category of the physiological information category. That is, factors belonging to the age category (e.g., Age) and multiple factors belonging to the lip color category of the color information category (e.g., L * , C * , and h) were used as input factors, and factors included in the physiological information category (e.g., MI) were obtained as output factors. MI obtained as output factor belongs to the pigment category of the physiological information category, and L used as input factor * , C * , and h belong to a category different from the lip color category of the color information category, and the age category of the physiological information category, to which Age belongs, and the output factor belongs to a category different from the category to which the input factor belongs. Note that "different categories" means that the category to which the input factor belongs and the category to which the output factor belongs are different from the category to which the input factor belongs, with respect to 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 category, lip tactile category, lip somatosensory category, body visual category, body tactile category, body somatosensory category, lip color category, or body color category. As shown in Figure 14, the R 2 The value was 0.92, clearly demonstrating a correlation. Therefore, by inputting the user's measured values ​​corresponding to the above input factors into the explanatory variables of the multiple regression equation shown in Figure 14, it is possible to determine the user's MI.

[0062] <Implementation pattern 6> FIG. 15 shows an overview of implementation pattern 6. In implementation pattern 6, the EI belonging to the pigment category of the physiological information category was calculated based on a multiple regression equation created using measurements from a population (85 people in this embodiment). The variables in the multiple regression equation were selected based on domain knowledge. In implementation pattern 6, the input factors were FAI, which belongs to the blood flow category of the physiological information category, a factor belonging to the color type category of the physiological information category (e.g., color group A: corresponding to pink type, pale type, purple type, and brown type), and the user's measured value (three variables) of height, which belongs to the body category of the physiological information category, and a factor included in the physiological information category (e.g., EI) was obtained as the output factor. In other words, multiple factors including one or more factors belonging to the physiological information category from the physiological information category and the body category were used as input factors. Furthermore, the EI obtained as the output factor belongs to the pigment category of the physiological information category and is a factor belonging to a category different from the blood flow category to which FAI belongs, the color type category to which color group A belongs, and the body category to which height belongs, which were used as input factors. As shown in Figure 15, the R 2 The value was 0.57, clearly demonstrating a correlation. Therefore, by inputting the user's measured values ​​corresponding to the above input factors into the explanatory variables of the multiple regression equation shown in Figure 15, it is possible to calculate the user's EI.

[0063] As described above, this method can calculate various output factors based on various input factors and various mathematical models. As in implementation patterns 1 to 3, by calculating multiple elements and their ratios and determining which elements are most likely, or elements that are not the most likely but have a certain degree of possibility, the results can be used to suggest makeup products or skin care methods more appropriately than if a single element were calculated. On the other hand, as in implementation patterns 4 to 6, depending on the type of factor, calculating a single element may be appropriate. In this way, the input factors and mathematical models can be determined depending on the output factors to be calculated and how the calculated output factors will be used. Furthermore, for example, it is possible to calculate a specific factor as an output factor even if user measurements for all of the factors listed in Table 2 are not available.

[0064] <Lip Evaluation System 10> A lip evaluation system 10 will be described which executes the lip evaluation method described above and evaluates the lip or physical features of a subject using factors different from the input factors as output factors. Fig. 16 shows a conceptual diagram of the lip evaluation system 10. The lip evaluation system 10 (hereinafter also referred to as the present system) is an information processing terminal capable of executing various processes, and includes a memory 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 also includes an input device such as a keyboard and pointing device, an arithmetic processing unit, a memory unit, a display device, etc.

[0065] The storage unit 11 is a storage means for storing a mathematical model that is obtained in advance from a population and indicates correlations between multiple input factors and output factors. In addition to the mathematical model, the storage unit 11 also stores programs and data required to execute the present method. The input unit 12 is an input means for inputting a plurality of input factors acquired from the subject, and corresponds to an input device provided in the information processing terminal. The calculation unit 13 is a calculation means for calculating output factors based on a mathematical model and input factors, and corresponds to an arithmetic processing unit provided in the information processing terminal. The output unit 14 is an output means for outputting the calculated output factors. This corresponds to outputting to a display device provided in the information processing terminal, but also includes outputting to a device or system other than the lip evaluation system 10 or outputting to a printer. The evaluation unit 15 is an evaluation means that uses the output factors to suggest makeup products and lip care products, and makeup methods and care methods. It corresponds to a calculation processing device provided in the information processing terminal. Depending on the output factors calculated by the calculation unit 13, the evaluation unit 15 may, for example, extract and suggest a recommended lip cosmetic from among multiple lip cosmetics with different color patterns, or extract and suggest a recommended lip care method from among multiple lip care methods.

[0066] Here, we will explain the lip cosmetics recommended when the corresponding ratios of the multiple elements constituting the color group A factor are determined as output factors using implementation pattern 1 or 2. The lip cosmetics recommended in this embodiment are lip cosmetics (makeup products) that are applied to the lips, such as lipstick, colored lip balm, lip gloss, lip pencil, lip liner, and powder lip. Table 3 shows the recommended makeup product types for each color type.

[0067] [Table 3]

[0068] Makeup products are intended to be enjoyed by beautifully changing the color of lips, but a common finish is often to impart a reddish hue to improve the facial impression. In this embodiment, we propose a makeup product that is applied to bare lips to impart a reddish hue. The pink type has a bright red lip color, so it doesn't matter what type of makeup product you choose. You can simply suggest that the user choose makeup products based on their preferences. Since the pale type has a lip color that is not reddish, low-coverage makeup products will result in the color of your bare lips, i.e., the color of your lips that is not reddish, even when you apply makeup, so low-coverage makeup products are not recommended. The purple type has a lip color with low saturation, so even if makeup is applied with low saturation or low coverage makeup products, the lip color will end up being the natural lip color, that is, a lip color with low saturation and no reddishness, so low saturation or low coverage makeup products are not recommended. Since the brown type has a dark lip color, high-brightness makeup products, low-saturation makeup products, and low-coverage makeup products will result in the natural lip color, i.e., a dark, dull lip color, even when applied, so high-brightness makeup products, low-saturation makeup products, and low-coverage makeup products are not recommended.

[0069] Next, we will explain the recommended care method when the ratio of each of the multiple elements that make up the color group A factor is obtained as the output factor using implementation pattern 1 or 2. Table 4 shows recommended care methods for each color type.

[0070] [Table 4]

[0071] Generally, bright red lips are considered to be healthy and beautiful. Lips with a bright red lip color have good blood flow, reach the periphery, and contain little melanin. Therefore, in this embodiment, we will propose a care method aimed at achieving a bright red lip color. Here, care target: blood flow refers to care that improves blood flow to the lips, and includes massage, moisturizing care, hot compresses, lip packs, carbonated preparations, warming preparations, etc. Care target: melanin refers to care to reduce melanin pigment, and includes care agents that reduce melanin pigment, cleansing agents, UV protection preparations, brightening preparations, etc. Pink types have good blood flow and little melanin pigment, so you can suggest that there is no need for blood flow care or melanin care. However, there is no problem with taking preventative measures such as blood flow care or melanin care, even if they are not necessary. Pale types have less melanin pigment, but have poor blood flow, making it difficult for blood to reach the extremities, so blood flow care should be recommended. The purple type has little melanin pigment, but has poor blood flow and does not reach the extremities, so blood flow care should be recommended. Brown types have a lot of melanin pigment, so melanin pigment care should be recommended.

[0072] Next, the difference between the makeup product suggestions and the care method suggestions when the output factors are calculated in the careful mode and when they are calculated in the simple mode will be described. Table 5 shows the differences in the makeup product suggestions and care method suggestions between the thorough mode and the simple mode.

[0073] [Table 5]

[0074] In the careful mode of Table 5, when suggesting makeup products, if the ratio is 60% or more, the makeup product types shown in Table 3 are recommended; if it is 30% or more but less than 60%, it is partially recommended; and if it is less than 30%, it is not recommended. Note that partial recommendation means that within that type of makeup, some products are recommended and some are not, depending on the color. Furthermore, when suggesting skin care methods, if the ratio is 60% or more, the skin care methods shown in Table 4 are actively recommended; if it is 30% or more but less than 60%, it is recommended; and if it is less than 30%, it is recommended as a preventative measure. As is clear from Table 5, even for the same user, the makeup products and skin care methods recommended will differ depending on whether the search is made in thorough mode or simple mode. As mentioned above, there is no clear boundary between lip color types, so if there are multiple possible color types, it is possible to make a wider range of suggestions that are more suited to lip color by recommending makeup products and skin care methods according to the proportions to which each of the multiple elements that make up the output factor applies, rather than specifying one of the multiple elements that make up the output factor. Furthermore, if a recommended care method is performed based on the output factors calculated in the careful mode, and the output factors are calculated again in the careful mode after a specified period of time, the ratio may change even if the type (color type) of the output factors remains unchanged. And, due to the change in ratio, the recommended makeup products and care methods may also change. In this way, by calculating the output factors in the careful mode and proposing recommended makeup products and care methods based on the ratio, it is possible to make appropriate suggestions during the process of lip color change (improvement).

[0075] <Modification> In this embodiment, recommended makeup products are suggested based on the output factors, but recommended makeup methods may also be suggested based on the output factors.Furthermore, while recommended skin care methods are suggested based on the output factors, recommended skin care products may also be suggested based on the output factors.

[0076] It is possible to calculate the ratio of the likelihood of each of the elements (pink type, pale type, purple type, and brown type) that make up color group A belonging to the color type category based on a Gaussian Naive Bayes model created using measurements from a population (85 people in this embodiment) using combinations of input factors other than those used in Implementation Pattern 1 and Implementation Pattern 2. Table 6 shows other examples of combinations of input factors.

[0077] [Table 6]

[0078] Combination 1 in Table 6 is Implementation Pattern 2, and combination 9 is Implementation Pattern 1. As is clear from Table 6, the generalization performance for the test data is high for all combinations. Furthermore, combinations 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, but the generalization performance for the test data is higher when factors belonging to the physiological information category are included as input factors (combinations 1 to 6, 9 and 10). Therefore, using factors belonging to the physiological information category as input factors enables lip evaluation with higher accuracy.

[0079] The lip evaluation system may be provided with a photographing device that photographs the user's lips, and values ​​serving as input factors may be measured and input from the image photographed by the photographing device. This makes it possible to evaluate the lip condition at the time of the desired evaluation. Alternatively, a photographed image of the user's lips may be acquired outside the lip evaluation system, and values ​​serving as input factors may be measured and input from the acquired image. This allows, for example, a lip image photographed by the user to be sent to the lip evaluation system, and evaluation may be performed based on that data, thereby improving convenience.

[0080] In the lip evaluation system of this embodiment, the values ​​of the input factors are input by the input means, but this is not limiting. For example, as described above, the values ​​of the input factors may be measured from an image captured by a photographing device or an acquired image and input into the calculation means, and this input process may also be the input means. [Explanation of symbols]

[0081] 10 Lip Evaluation System 11 Storage section 12 Input section 13 Calculation section 14 Output section 15 Evaluation Section

Claims

1. A method for evaluating a feature of a subject's lips or body by using a plurality of factors including one or more factors belonging to a physiological information category as input factors and a factor different from the input factors as an output factor from a category group consisting of a physiological information category having a factor being a physiological feature related to the lips or body of the subject, a sensory information category having a factor being a sensory feature related to the lips or body of the subject, and a color information category having a factor being color information related to the lips or body of the subject, the method comprising the steps of: A lip evaluation method, comprising the steps of: determining the output factor based on a mathematical model that is obtained in advance from a population and shows a correlation between the plurality of input factors and the output factor; and determining the output factor based on the plurality of input factors obtained from the subject.

2. The physiological information categories include a pigment category using lip pigment information as a factor, a blood flow category using lip blood flow information as a factor, a blood vessel category using lip blood vessel information as a factor, a shape category using lip shape information as a factor, a surface shape index category using lip surface shape index information as a factor, a color type category using lip color type information as a factor, a body category using the physiological characteristics of the subject's body as a factor, an age category using the subject's age information as a factor, or a gender category using the subject's gender information as a factor, The sensory information categories include a lip visual category having lip visual information as a factor, a lip tactile category having lip tactile information as a factor, a lip somatosensory category having lip somatosensory information as a factor, a body visual category having body visual information as a factor, a body tactile category having body tactile information as a factor, or a body somatosensory category having body somatosensory information as a factor, 2. The lip evaluation method according to claim 1, wherein the color information categories include a lip color category in which lip color information is a factor, or a body color category in which body color information is a factor.

3. A factor belonging to the physiological information category and a factor belonging to the color information category are set as the input factors; 3. The lip evaluation method according to claim 2, wherein factors belonging to the color type category are obtained as the output factors.

4. the input factors belong to any one of 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, the lip visual category, the lip tactile category, the lip somatosensory category, the body visual category, the body tactile category, the body somatosensory category, the lip color category, and the body color category; 4. The lip evaluation method according to claim 2, wherein the output factors belong to a category different from a category to which the input factors belong.

5. A plurality of factors included in the physiological information category and a factor belonging to the color information category are set as the input factors; 4. The lip evaluation method according to claim 2, wherein a factor belonging to the age category is obtained as the output factor.

6. A factor belonging to the age category and a plurality of factors belonging to the color information category are used as the input factors; 4. The lip evaluation method according to claim 2, wherein factors belonging to the physiological information category are obtained as the output factors.

7. Each of the factors is composed of a plurality of elements that indicate the degree of the factor or classify the factor, The lip evaluation method according to any one of claims 1 to 3, characterized in that the mathematical model is used to classify and output the plurality of elements constituting the output factor based on the plurality of input factors according to their corresponding ratios.

8. 4. The lip evaluation method according to claim 1, further comprising the step of extracting a recommended lip cosmetic from among a plurality of lip cosmetics having different color patterns, in accordance with the determined output factor.

9. 4. The lip evaluation method according to claim 1, further comprising the step of extracting a recommended lip care method from among a plurality of lip care methods in accordance with the determined output factor.

10. A system for evaluating the characteristics of the lips or body of a subject using a plurality of factors as input factors, including one or more factors belonging to a physiological information category, from a category group consisting of a physiological information category having a factor being a physiological characteristic related to the lips or body of the subject, a sensory information category having a factor being a sensory characteristic related to the lips or body of the subject, and a color information category having a factor being color information related to the lips or body of the subject, and using a factor different from the input factor as an output factor, the system comprising: A storage means for storing a mathematical model that is obtained in advance from a population and indicates a correlation between the plurality of input factors and the output factors; an input means for inputting the plurality of input factors obtained from the subject; a calculation means for calculating the output factor based on the mathematical model and the input factor.

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