Lip evaluation method

Abstract

This technology provides an evaluation method for the characteristics of a subject's lips or body, using multiple factors, each containing one or more factors belonging to the subject's physiological information category, as input factors, and a factor different from the input factors as the output factor. [Solution] The lip evaluation method evaluates the characteristics of a subject's lips or body by using multiple factors, including one or more factors belonging to the physiological information category, as input factors, and factors different from the input factors as output factors, from a group of categories consisting of a physiological information category with physiological characteristics relating to the subject's lips or body as factors, a sensory information category with sensory characteristics relating to the subject's lips or body as factors, and a color information category with color information relating to the subject's lips or body as input factors. The output factors are determined based on a mathematical model obtained in advance from a population that shows the correlation between multiple input factors and output factors, and multiple input factors obtained from the subject.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Patent Document 1, the lip color of a user is classified into lip color categories based on lightness, chroma, and hue using a lip color scale. However, in the process of further research, there is a possibility that it may not be sufficient to classify only based on information related to color such as lightness, chroma, and hue, and there is room for improvement.

[0005] The present invention has been made in view of the above problems, and relates to a lip evaluation method for evaluating lips using information belonging to a physiological information category that takes into account physiological characteristics of the lips of a subject or physiological information such as the age of the subject.

Means for Solving the Problems

[0006] The present invention relates to a method for evaluating the characteristics of a subject's lips or body, using a group of categories consisting of a physiological information category with factors relating to the physiological characteristics of the subject's lips or body, a sensory information category with factors relating to the sensory characteristics of the subject's lips or body, and a color information category with factors relating to the color information of the subject's lips or body, as input factors, which include one or more of the factors belonging to the physiological information category, and using factors different from the input factors as output factors, wherein the output factors are determined based on a mathematical model obtained in advance from a population that shows the correlation between the plurality of input factors and the output factors, and a plurality of the input factors obtained from the subject.

[0007] The present invention also relates to a lip evaluation system for evaluating the characteristics of a subject's lips or body, which includes, as input factors, one or more factors belonging to the physiological information category, from a group of categories consisting of a physiological information category with physiological characteristics relating to the subject's lips or body as factors, a sensory information category with sensory characteristics relating to the subject's lips or body as factors, and a color information category with color information relating to the subject's lips or body as factors, and is characterized by including a storage means for storing a mathematical model obtained in advance from a population that shows the correlation between the plurality of input factors and the output factor, an input means for inputting the plurality of input factors obtained from the subject, and a calculation means for determining the output factor based on the mathematical model and the input factors. [Effects of the Invention]

[0008] The method provided by the present invention makes it possible to evaluate the lips using information belonging to the physiological information category, thereby enabling lip evaluation using multifaceted information. [Brief explanation of the drawing]

[0009] [Figure 1](a) A diagram showing the color characteristics of a pink-type lip color, (b) A diagram showing the color characteristics of a pale-type lip color, (c) A diagram showing the color characteristics of a purple-type lip color, and (d) A diagram showing the color characteristics of a brown-type lip color. [Figure 2] (a) This figure shows the distribution of L* (lightness) of lips by lip color type, (b) This figure shows the distribution of C* (saturation) of lips by lip color type, and (c) This figure shows the distribution of h (hue) of lips by lip color type. [Figure 3] This figure shows the percentage of subjects by lip color type, broken down by age group. [Figure 4] This diagram shows the relationship between lip color type and melanin index. [Figure 5] This diagram shows the relationship between lip color types and ATI (Area of ​​Blood Flow). [Figure 6] This figure shows an example of an MBR time waveform. [Figure 7] This is a diagram showing the different parts of the lips. [Figure 8] This figure shows the correlation between lip color and body visual categories. [Figure 9] This flowchart shows the lip evaluation method. [Figure 10] This diagram shows an overview of implementation pattern 1. [Figure 11] This diagram shows an overview of implementation pattern 2. [Figure 12] This diagram shows an overview of implementation pattern 3. [Figure 13] This diagram shows an overview of implementation pattern 4. [Figure 14] This diagram shows an overview of implementation pattern 5. [Figure 15] This diagram shows an overview of implementation pattern 6. [Figure 16] This is a conceptual diagram of a lip information evaluation system. [Modes for carrying out the invention]

[0010] Hereinafter, examples of preferred embodiments of the present invention will be described with reference to the drawings. Note that the drawings of these embodiments are for illustrative purposes only, illustrating the technical concept, configuration, and operation of the present invention, and do not specifically limit its configuration. Furthermore, in all drawings, similar components are denoted by the same reference numerals, and redundant explanations are omitted as appropriate.

[0011] <Overview> An overview of the lip evaluation method in this embodiment will be described. The lip evaluation method of this embodiment (hereinafter sometimes referred to as "this method") is a method for evaluating the characteristics of a subject's lips or body, using a group of categories consisting of a physiological information category with physiological characteristics relating to the subject's lips or body as factors, a sensory information category with sensory characteristics relating to the subject's lips or body as factors, and a color information category with color information relating to the subject's lips or body as input factors, with one or more factors belonging to the physiological information category as input factors, and a factor different from the input factors as the output factor, characterized in that the output factor is determined based on a mathematical model obtained in advance from a population that shows the correlation between the plurality of input factors and the output factor, and a plurality of input factors obtained from the subject.

[0012] Until now, when classifying lip color, the classification has been based solely on differences in lip color information such as lightness, 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 the characteristics of lip blood flow, lip shape, and the age of the subject. The inventors of this invention have come to the realization that it is important to consider physiological information in addition to lip color information such as lightness, saturation, and hue. Therefore, we propose a lip evaluation method that evaluates lips using information belonging to a physiological information category that uses physiological characteristics related to the subject's lips or body as factors.

[0013] This lip evaluation method evaluates the lips using multiple factors, including one or more factors belonging to the physiological information category, from among numerous factors belonging to the physiological information category, numerous factors belonging to the sensory information category, and numerous factors belonging to the color information category. To facilitate understanding of the present invention, among the color group factors that can be 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 * (lightness), C * We will provide a detailed explanation of the correlation between (saturation) and h (hue), and then explain each factor and each category.

[0014] Figure 1 shows the results of classifying the lip color (mainly the lower lip) of 85 Japanese women aged 20 to 70. The evaluation was performed visually by three expert evaluators familiar with lip color. First, similar lip colors were classified to minimize the number of types (1st round). After a predetermined number of days, the same photographs were used for a second round of evaluation to determine the final color classification. If the results differed between the 1st and 2nd rounds, a re-evaluation was performed. As a result of the evaluation, as shown in Figure 1, the lip color of Japanese women can be classified into four types. In this specification, each is given a provisional color name and will be described as (a) pink type, (b) pale type, (c) purple type, and (d) brown type. However, there are no clear boundaries, and it is common for a lip to possess multiple types, for example, being both pink and pale. Here, "no clear boundaries" means that the color information (L) of the four groups is not clearly defined. * , C * The terms , h, etc., have different central values, but they are not completely separate without overlap; there are overlapping regions. Here, we will explain the characteristics of each type.

[0015] Figure 1(a) The pink type has a bright red lip color. Also, L * It is on the higher side, C * is relatively high, while h is relatively low. The color of the lip type in Fig. 1(b) has no red tint. Also, L * is high, C * is low, and h is high. The color of the lip type in Fig. 1(c) has low saturation. Also, L * is high, C * is low, and h (hue) is low. The color of the lip type in Fig. 1(d) is a dark lip color. Also, L * is low, C * is low, and h is high.

[0016] Figs. 2(a) to (c) show, based on the determination results of Fig. 1, what color types are distributed for what values of L * , C * , and h respectively. Fig. 2(a) is a diagram showing the distribution of the L * of the lips of the subjects 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), there is no significant difference in the values of L * distributed among the pink type, the pale type, and the purple type. However, for the brown type, L * is mostly distributed at low values. There is no significant difference among 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 also between the pink type and the brown type, and between the pale type and the brown type. Fig. 2(b) is a diagram showing the distribution of the C * of the lips of the subjects 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), for the pink type, the distributed C * is distributed at high values, while for the pale type, the purple type, and the brown type, the distributed C * is mostly distributed at low values. The pink type has a significant difference from other types, and there is also a significant difference 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 values ​​for the subjects' lips by color type. The horizontal axis represents the 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 lower h values, while the pale and brown types have higher 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 each color type among subjects by age group. The horizontal axis represents age, and the vertical axis represents the proportion of subjects belonging to each color type. For example, the proportion of pink types is high among those in their 20s, and the proportion of purple types is high among those in their 70s. Also, the proportion of pink types decreases with increasing age. Thus, the proportion of subjects belonging to each color type differs depending on age.

[0018] Figure 4 shows the distribution of melanin index (MI) in the subjects' lips by color type. The horizontal axis represents the color type, and the vertical axis represents the MI. Among the four types, the pink, pale, and purple types are distributed at low MI values, while the brown type is distributed at high MI values. The brown type shows a statistically significant difference from the pink, pale, and purple types.

[0019] Figure 5 shows the ATI (Area of ​​Blood Flow Peak) for each color type. A lower ATI indicates that the time to reach the peak is shorter. The pink type indicates that blood flow reaches the peak quickly, while the pale and purple types reach the peak later. Table 1 summarizes the information from Figures 1 to 5.

[0020] [Table 1]

[0021] As shown in Table 1, the factors (L) belonging to the color information category * , C *By classifying lip color into types using factors (MI, ATI) belonging to the physiological information category and the characteristics estimated from them, it becomes possible to make suggestions that take into account the physiological information factors that are influencing lip color information when proposing makeup methods, makeup products, care methods, and care products based on the classification results. For this reason, in this method, for example, information belonging to the physiological information category that has the physiological characteristics of the subject's lips or the subject's age as factors is also used to evaluate the lips.

[0022] Next, we will explain each factor used in this lip evaluation method, and the categories to which each factor belongs. 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 consist of a "physiological information category" with factors relating to the physiological characteristics of the subject's lips or body, a "sensory information category" with factors relating to the sensory characteristics of the subject's lips or body, and a "color information category" with factors relating to the color information of the subject's lips or body. The "physiological information category," "sensory information category," and "color information category" each include factors relating to the lips and factors relating to areas other than the lips. In this embodiment, the major classifications are the "physiological information category," the "sensory information category," and the "color information category," and the subclasses are the "pigment category," "blood flow category," "vascular category," "shape category," "surface shape index category," "color type category," "body category," "age category," and "gender category" belonging to the "physiological information category," the "lip visual category," "lip tactile category," "lip somatosensory category," "somatosensory category," "somatosensory category," and "somatosensory category" belonging to the "sensory information category," and the "lip color category" and "body color category" belonging to the "color information category." Furthermore, as will be explained in more detail later, factors belonging to the intermediate categories may consist of multiple elements, such as a single element like the measured value itself, a numerical range (for example, for age, a range like 10s, 20s, etc.), or a degree of perception (for example, for complexion, strongly applicable / applicable / not applicable). When composed of multiple elements, the numerical range set for each factor may consist of multiple elements indicating the degree of the factor, or each set stage, such as strongly applicable / applicable / not applicable, may consist of multiple elements indicating the degree of the factor. In addition, for example, in the case of each factor belonging to the color type category, it may consist of elements determined by visual evaluation (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 body belong. In this embodiment, the factors of physiological characteristics are further categorized according to their characteristics. These categories include a "pigmentation category" with lip pigment information as a factor, a "blood flow category" with lip blood flow information as a factor, a "vascular 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 the physiological characteristics of the subject's body as a factor, an "age category" with the subject's age information as a factor, or a "gender category" with 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 of the lip color category (L * While it naturally correlates with other factors, the amount of pigment is a physiological characteristic, so the pigment category belongs to the "physiological information category." In this embodiment, MI (melanin index) and EI (erythrism 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, in cases of low MI (Minor Intake), lip color becomes more dependent on hemoglobin levels. Furthermore, each factor belonging to the pigment category is composed of elements, with a numerical range set for each factor in addition to the measured value itself.

[0027] The "blood flow category" includes MBR (Mean Blur Rate): blood flow rate, Fluctuation: rate of variation of blood flow, Skew: bias of blood flow waveform, BOS (Blowout Score): steady blood flow, BOT (Blowout Time): persistence of high blood flow, Rising rate: time variation of blood flow rise rate, Falling rate: time variation of blood flow fall rate, FAI: maximum upward acceleration during blood flow rise, ATI: blood flow peak position, and RI (Resistivity Index): peripheral vascular resistance. In addition to the measured values ​​themselves, each factor belonging to the blood flow category is composed of elements with a set numerical range for each factor.

[0028] MBR is relative blood flow, and is obtained, for example, by applying the mean MBR value to the linear regression equation blood flow mL / (min·100g) = 41.7 × MBR value - 15.1. Fluctuation is an index that shows the coefficient of variation of the MBR. Skew is a value that indicates the bias in the blood flow waveform. BOS is a value that indicates steady blood flow. BOT is an indicator of the persistence of a high MBR value, and the BOT value is expressed by the following formula using the half-width (time) (W) and single-beat width (time) (F) of the MBR value shown in Figure 6, and the proportionality constant "C". (BOT) = C·(W) / (F) The rising rate is an indicator that shows the temporal variation in the rate of increase in blood flow. The Falling rate is an index that shows the time variation of the rate of decrease 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. Below, "C" is the proportionality constant. (Falling rate) = C·(S²) / (Sall) FAI indicates the instantaneous maximum blood flow during an increase in blood flow. ATI is the percentage of a single heartbeat that takes time to reach the maximum MBR value (MBRmax in Figure 6) of the MBR time waveform. RI is an index of peripheral vascular resistance, and the RI value is obtained by dividing the difference between the maximum MBR value (MBRmax in Figure 6) and the minimum MBR value (MBRmin in Figure 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 of the factors—area, width, length, density, and branching—is measured using not only the measured values ​​themselves from lip image data, but also by setting a numerical range for each factor, with each range forming an element.

[0030] The "Shape Category" includes the curvature width of the upper lip's white portion, the length of the upper lip's white portion, the fullness width of the lower lip's red portion, and the vertical and horizontal width of the red portion. Figure 7 shows the lengths, widths, and other parts of each factor in the Shape Category. Factors belonging to the Shape Category consist of the values ​​of each part shown in Figure 7, as well as numerical ranges set for each factor, with each range being used as an element. Although not shown in Table 2, other types such as thin lip type, thick lip type, type with only the upper lip being thick, and type with only the lower lip being thick are also acceptable.

[0031] The "Surface Shape Index Category" includes categories derived from wrinkles and peeling. Wrinkle-derived values ​​are obtained from surface irregularities such as depth, length, and width. Peeling-derived values ​​are obtained from the non-uniformity of fine surface irregularities. Factors belonging to the Surface Shape Index Category consist of the obtained values ​​themselves, as well as a numerical range set for each factor, with each range being constructed as an element.

[0032] The "color type category" includes color group A, which consists of the aforementioned "pink type" element, "pale type" element, "purple type" element, and "brown type" element, as well as the color pink group, which consists of dark pink type element and light pink type element. In this embodiment, the determination of the elements that make up each color group, which are factors, is, for example, by measuring L that belongs to the lip color category. * a * (The larger the positive value, the closer it is to red; the larger the negative value, the closer it is to green; the value becomes more vivid as the absolute value increases), b *(The larger the positive value, the closer it is to yellow; the larger the negative value, the closer it is to blue; the value becomes more vivid as the absolute value increases), C * This is done by clustering using the h value and Age, which belongs to the age category. As mentioned above, as age changes, the color of the lips becomes less red and closer to brown, so L * a * , b * , C * It is preferable to consider not only factors belonging to the lip color category, such as h, but also factors belonging to the age category (Age) when making the determination. In this embodiment, since the age category factors included in the physiological information category are used to determine the elements of each color group in the color type category, the "color type category" is included in the physiological information category. Note that if the age category factors are not used to determine the elements of each color group, only the apparent color (lip color category factors (L)) is considered. * If only (etc.) is used, color group A may be included in the lip color category.

[0033] A "body category" is a category to which factors related to physical information, such as height, weight, BMI (Body Mass Index), blood pressure, and heart rate, belong. In addition to the obtained values ​​themselves, a numerical range is set for each factor, and each range is constructed as an element. An "age category" refers to the age itself or a specific age group (e.g., 20s, 30s). When age is used as a factor, for example, 20s, 30s, 40s, etc., are elements that make up an age group. A "gender category" uses gender as a factor, and the elements that constitute gender may include not only male and female, but also elements such as masculine and feminine traits.

[0034] The "sensory information category" is a category to which factors relating to the subject's lips and body belong. In this embodiment, the factors of sensory characteristics are further categorized for each characteristic. These categories include the "lip visual category" with visual information as a factor for the lips, the "lip tactile category" with tactile information as a factor for the lips, the "lip somatosensory category" with somatosensory information as a factor for the lips, the "body visual category" with visual information as a factor for the body, especially the face, neck, and décolleté close to the lips, the "body tactile category" with tactile information as a factor for the body, especially the face, neck, and décolleté close to the lips, or the "body somatosensory category" with somatosensory information as a factor for the body, especially the face, neck, and décolleté close to the lips.

[0035] Here, I will explain the results of an experiment conducted on the influence of lip color on physical impression (facial impression). <Experimental Method> 31 participants 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 Scheffé's paired comparison method (Ura's modified method). Evaluation criteria: 1) Bright complexion 2) Good complexion 3) Clear skin 4) Attractive (rated on a 5-point scale) Stimulation: Only the lip color is L compared to the average face of a woman in her 40s (original image). * a * , b * Seven stimulus images, each varying by ±5 based on a color system. Note that the skin tone in images A through G is the same; only the lip color is altered. Figure 8 shows the experimental results.

[0036] From Figure 8, for example, the L of the lips * Increasing the value makes the complexion appear "brighter," and the L of the lips * It is clear that reducing the value makes the complexion appear less bright, and the L of the lips * It can be said that there is a relationship between the value of and whether or not one's complexion appears bright. Similarly, for example, the a of the lips * Increasing the value makes the complexion appear "brighter," and the lips...* It is clear that reducing the value makes the complexion appear less bright, and the lip 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 L of the lips * It is clear that reducing the value makes the complexion "not look good," and the L of the lips * It can be said that there is a relationship between the value and whether or not the complexion looks good. Similarly, for example, the a of the lips * Increasing the value makes the complexion "feel better," and the lips a * It is clear that reducing the value makes the complexion "not look good," and the lip a * It can be said that there is a relationship between the value and whether or not one's complexion appears healthy. Similarly, for example, the L of the lips * It is clear that reducing the value makes the skin "not feel beautiful," and the L of the lips * It can be said that there is a relationship between the value and whether or not the skin feels beautiful. Similarly, for example, the a of the lips * Increasing the value makes the skin "feel more beautiful," and the lips * It is clear that reducing the value makes the skin "not feel beautiful," and the a of the lips * It can be said that there is a relationship between the value and whether or not one's skin feels beautiful. Similarly, for example, the L of the lips * It is clear that making the value smaller makes it "less attractive," and the L of the lips * It can be said that there is a relationship between value and whether or not something is perceived as attractive. Similarly, for example, the a of the lips * Increasing the value makes it seem more attractive, and the lips * It is clear that making the value smaller makes it "not feel attractive," and the a of the lips * It can be said that there is a relationship between value and whether or not something is perceived as attractive. Thus, it is clear that there is a relationship between lip color (lip color category) and the visual perception category, and it is also clear that the visual perception of the face differs simply by changing the lip color, without changing the complexion.

[0037] The "Lip Visual Perception Category" includes factors such as rosiness, transparency, brightness, good color, beauty, and attractiveness. Rosiness is how the subject or other subjects perceive the rosiness of the lips when they look at them, and consists of elements such as: looks rosy (applies) / doesn't look rosy (looks bad (doesn't apply)). Transparency is how the subject or other subjects perceive the transparency of the lips when they look at them, and consists of elements such as: looks transparent (applies) / doesn't look transparent (doesn't apply). Brightness is how the subject or other subjects perceive the brightness of the lips when they look at them, and consists of elements such as: looks bright (applies) / doesn't look bright. Good color is how the subject or other subjects perceive the good color of the lips when they look at them, and consists of elements such as: good color (applies) / bad color (doesn't apply) "Beautiful" refers to how the subject or other subjects perceive the lips as beautiful, and consists of elements such as "looks beautiful" or "does not look beautiful" (not applicable). "Attractive" refers to how the subject or other subjects perceive the lips as attractive, and consists of elements such as "looks attractive" (applies) or "does not look attractive" (not applicable). In this embodiment, all factors included in the visual perception category consist of two elements: "applies" or "does not apply," but this is not limited to this, and all factors may consist of three elements: "strongly agree," "applies," or "does not apply." Alternatively, some factors may consist of two elements, while others consist of three elements.

[0038] The "lip tactile sensation category" includes factors such as roughness and elasticity. Roughness consists of two elements: whether the subject or another subject felt roughness when touching their lips (applies) / whether they did not feel roughness (does not apply). Elasticity consists of two elements: whether the subject or another subject felt elasticity when touching their lips (applies) / whether they did not feel elasticity (does not apply). In this embodiment, all factors included in the tactile sensation category consist of two elements: apply / do not apply, but this is not limited to this, and all factors may consist of three elements: very apply, apply, or do not apply. Alternatively, some factors may consist of two elements and others of three elements.

[0039] The "oral somatosensory category" includes factors such as tightness and dryness. Tightness is comprised of two elements: whether the subject felt their lips were tight (applies) or not (does not apply). Dryness is comprised of two elements: whether the subject felt their lips were dry (applies) or not (does not apply). In this embodiment, all factors included in the somatosensory category consist of two elements: apply / does not apply, but this is not limited to this, and all factors may consist of three elements: very apply, apply, or do not apply. Alternatively, some factors may consist of two elements and others of three elements.

[0040] The "Body Perception Category" includes factors such as rosiness, clarity, brightness, good color, beauty, and attractiveness. Rosiness is how the subject or other subjects perceive the body's rosiness when they look at it, and consists of elements such as "looks rosy" (applies) / "looks rosy" (looks bad (does not apply)). Clarity is how the subject or other subjects perceive the body's clarity when they look at it, and consists of elements such as "looks radiant" (applies) / "does not look radiant" (does not apply). Brightness is how the subject or other subjects perceive the body's brightness when they look at it, and consists of elements such as "looks bright" (applies) / "does not look bright" (does not apply). Good color is how the subject or other subjects perceive the body's good color when they look at it, and consists of elements such as "good color" (applies) / "bad color" (does not apply) "Beauty" refers to how the subject or other subjects perceive beauty when they see the lips, and consists of elements such as "looks beautiful" or "does not look beautiful" (not applicable). "Attractive" refers to how the subject or other subjects perceive attractiveness when they see the body, and consists of elements such as "looks attractive" (applies) or "does not look attractive" (not applicable). In this embodiment, all factors included in the body perception category consist of two elements: "applies" or "does not apply," but this is not limited to this, and all factors may consist of three elements: "strongly agree," "applies," or "does not apply." Alternatively, some factors may consist of two elements and others of three elements.

[0041] The "body tactile sensation category" includes factors such as roughness and elasticity. Roughness consists of two elements: whether the subject or another subject felt roughness when touching the body (applies) / whether they did not feel roughness (does not apply). Elasticity consists of two elements: whether the subject or another subject felt elasticity when touching the body (applies) / whether they did not feel elasticity (does not apply). In this embodiment, all factors included in the body tactile sensation category consist of two elements: apply / do not apply, but this is not limited to this, and all factors may consist of three elements: very apply, apply, or do not apply. Also, some factors may consist of two elements and others of three elements.

[0042] The "Somatosensory Category" includes factors such as tightness and dryness. Tightness is comprised of two elements: whether the subject felt their body was tight (applies) or not (does not apply). Dryness is comprised of two elements: whether the subject felt their body was dry (applies) or not (does not apply). In this embodiment, all factors included in the Somatosensory Category consist of two elements: apply / does not apply, but this is not limited to this, and all factors may consist of three elements: very apply, apply, or do not apply. Alternatively, some factors may consist of two elements and others of three elements.

[0043] The "Color Information Category" is a category to which factors of information used to identify the type of color based on color measurements taken of the subject's lips and body are included. Further categories are established for each target area, including the "Lip Color Category," which uses color information related to the lips as a factor, and the "Body Color Category," which uses color information related to the body, particularly the face, neck, and décolleté, which are close to the lips, as factors.

[0044] The lip color category is a category to which factors containing information used to identify the type of color based on the measured color of the lips or the measured color are included. In this embodiment, the following factors belong to the lip color category. L* This is brightness. a * The larger the positive value, the redder the color; the larger the negative value, the greener the color; and the color becomes more vivid as the absolute value increases. b * The larger the positive value, the more yellow it indicates, and the larger the negative value, the more blue it indicates. The colors become more vivid as the absolute value increases. C * This is saturation. h represents hue. R is a value related to the intensity of the long wavelength (red region) in RGB, a type of color representation. G is a value related to the intensity of the mid-wavelength (green region) in RGB, a type of color representation. B is a value related to the intensity of the short wavelength (blue region) in RGB, a type of color representation. A spectral distribution represents the relative proportion of each single color present in a given color. A color chart is a list of color samples created according to a set standard. Color difference is a value that represents the difference in color, for example, the difference between the red lip area and the white lip area. Color unevenness indicates spatial non-uniformity of color and is a value obtained from frequency, histogram shape (variance, skewness, kurtosis, etc.), and statistical quantities.

[0045] The body color category is a category to which factors containing information used to identify the type of color based on color measurements of the body or the color measurements themselves belong. In this embodiment, the factors belonging to the body color category are the same as those in the lip color category, so their explanation is omitted.

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

[0047] This method will be explained below. The "physiological information category with factors relating to the subject's lips or body" refers to the category to which factors relating to the physiological characteristics of the subject's lips and body belong, and includes the "pigmentation category" with factors relating to lip pigmentation information, the "blood flow category" with factors relating to lip blood flow information, the "vascular category" with factors relating to lip blood vessel information, the "shape category" with factors relating to lip shape information, the "surface shape index category" with factors relating to lip surface shape index information, the "color type category" with factors relating to lip color group information, the "body category" with factors relating to the subject's body physiological characteristics, the "age category" with factors relating to the subject's age information, or the "gender category" with factors relating to the subject's gender information. The "sensory information category with factors relating to the subject's lips or body" is a category to which factors relating to the subject's lips and body belong, and includes the "lip visual category" with visual information as a factor for the lips, the "lip tactile category" with tactile information as a factor for the lips, the "lip somatosensory category" with somatosensory information as a factor for the lips, the "body visual category" with visual information as a factor for the body, especially the face, neck, and décolleté close to the lips, the "body tactile category" with tactile information as a factor for the body, especially the face, neck, and décolleté close to the lips, or the "body somatosensory category" with somatosensory information as a factor for the body, especially the face, neck, and décolleté close to the lips. The "color information category with factors related to the subject's lips or body color information" refers to a category to which factors of color values ​​measured for the subject's lips and body, or information used to identify the type of color based on measured values, belong. This category includes the "lip color category," which has factors related to the lips' color information, and the "body color category," which has factors related to the body, particularly the face, neck, and décolleté, which are close to the lips. A "category group" consists of the following categories included in the physiological information category: "Pigment Category," "Blood Flow Category," "Vascular Category," "Shape Category," "Surface Shape Index Category," "Color Type Category," "Body Category," "Age Category," and "Gender Category"; the following categories included in the sensory information category: "Lip Visual Sensation Category," "Lip Tactile Sensation Category," "Lip Somatosensory Category," "Body Visual Sensation Category," "Body Tactile Sensation Category," and "Body Somatosensory Category"; and the following categories included in the color information category: "Lip Color Category" and "Body Color 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 characteristics of the subject's lips or body using a factor different from the input factor as the output factor" means that as long as a factor different from the input factor is output, the categories to which the input factor belongs and the categories to which the output factor belongs do not have to be the same or different. Furthermore, depending on the calculated output factor, the subject's lips or body characteristics are evaluated, such as external aspects like color and appearance, or internal aspects like blood flow. A "mathematical model that shows the correlation between multiple input and output factors obtained in advance from a population" is a mathematical model that shows the relationship between multiple input and output factors created from information obtained in advance from a population consisting of multiple subjects. Examples of mathematical models that output a single element or the value of a single element include thresholding based on summary statistics (location, variance, moment) from the population, multiple regression analysis, K-nearest neighbors, logistic regression, and regression trees. Examples of mathematical models that output multiple elements or the ratios of multiple elements include simple Bayesian classifiers, gradient boosting, support vector machines, neural networks, and deep learning. "Determining the output factor based on the multiple input factors obtained from the subjects" means determining the output factor based on the input factors and mathematical model described above.

[0048] Next, an overview of the processing flow of this method will be explained using Figure 9. As will be described in detail later, Figure 9 shows a processing flow in which both the value of one element or one element of the output factor to be obtained by this process and the values ​​of multiple elements and the ratios of multiple elements of the output factor to be obtained, are obtained. However, it is also possible to obtain only one of them. In this embodiment, obtaining the value of one element or one element of the output factor to be obtained is referred to as "deterministically obtaining," and obtaining the values ​​of multiple elements and the ratios of multiple elements of the output factor to be obtained is sometimes referred to as "obtaining as a ratio." Also, Figure 9 shows the calculation of the value of one element or one element of the output factor using a predetermined mathematical model and the calculation of multiple elements and the ratios of multiple elements using a predetermined mathematical model. In this embodiment, calculating the value of one element or one element using a predetermined mathematical model is referred to as "calculating in simplified mode," and calculating multiple elements and the ratios of multiple elements is sometimes referred to as "calculating in detailed mode."

[0049] Step S100 is the process of determining input and output factors. In this method, multiple factors, including factors included in the physiological information category of the lips, are used as input factors, and factors different from the input factors can be output. Therefore, input and output factors are determined, and output factors are determined based on the determined input factors. Any combination and type of input and output factors can be used, but the accuracy of the output factors obtained will differ depending on the input factors. Therefore, it is preferable that by determining the desired output factors, a combination and type of input factors with good accuracy will be automatically determined or recommended as factors.

[0050] Step S110 determines whether to determine the output factor of a single element or the value of a single element, or to determine the output factor of multiple elements and the ratio of multiple elements; in other words, whether to calculate in a simplified mode or in a detailed mode. This step may be determined automatically depending on the output factor to be determined. If the output factor of a single element or the value of a single element is to be determined, proceed to step S120; if the output factor of multiple elements and the ratio of multiple elements is to be determined, proceed to step S130.

[0051] Step S120 is the process of determining the output factors using the input factors determined in Step S100 and a mathematical model that determines the output factors for one element or the value of one element, if it was decided in Step S110 to determine the output factors in a simplified mode. The mathematical model shows the relationship between the input factors and the output factors from the population.

[0052] Step S130 is the process of determining the output factors using the input factors determined in Step S100 and a mathematical model that calculates multiple elements and their ratios, in the case where it was decided in Step S110 to determine the output factors in a careful mode. The mathematical model shows the relationship between the input factors and the output factors from the population.

[0053] Step S140 is a process of deciding whether to use the multiple elements and their ratios obtained in Step S130 to propose, for example, recommended care methods or makeup methods, or to identify a single output factor based on the obtained multiple elements and their ratios, and then propose recommended care methods or makeup methods using that identified output factor. This step may be determined automatically depending on the output factor to be obtained. Furthermore, it is preferable to decide which output factor to use depending on how the output factor will be used (e.g., suggesting care methods, suggesting makeup products).

[0054] Step S150 is the process of identifying one output factor if it was decided in step S140 to identify one output factor. Methods of identification include identifying the output factor with the highest / lowest ratio, or having staff or users at a store or similar location identify the output factor.

[0055] Step S160 is a process in which care methods and makeup products are suggested based on the output factors obtained in Step S120, Step S130, or Step S150. Note that this process is not included in the method because it utilizes the output factors obtained by this method. Also, Steps S110 and S140 may be automatically determined by determining the input and output factors in Step S100, so they may not be included in the method. Furthermore, this method may be in either the simple mode or the detailed mode.

[0056] Next, we will explain the lip evaluation performed using this method. Note that the implementation patterns shown below are examples. Implementation patterns 1 to 3 are examples of the meticulous mode, using a Gaussian naive Bayes model as a mathematical model to show the correlation between multiple input and output factors, and determining multiple elements and their ratios as output factors. Implementation patterns 4 to 6 are examples of the simplified mode, using a multiple regression equation as a mathematical model to show the correlation between multiple input and output factors, and determining the output factor for one element or the value of one element. Furthermore, each mathematical model was created in advance using the measured values ​​of the factors shown in Table 2 for the population of 85 people explained in Figure 1. When using the color information category factor as an input factor, the measured value of the user's bare lips is used. This allows for accurate evaluation of the user's lips. When using the color group (color type) as an input factor, the color type calculated in advance from the measured values ​​of the color information category factors and the measured values ​​of the factors included in the physiological information category should be used. Furthermore, for factors belonging to the shape category, it is sufficient to obtain a user's lip image in advance and use the measurements of each part taken from that lip image.

[0057] <Implementation Pattern 1> Figure 10 shows an overview of implementation pattern 1. In Implementation Pattern 1, the proportion of each element belonging to color group A of the color type category—pink type, pale type, purple type, and brown type—was calculated based on a Gaussian naive Bayes model created using measurements from the population (85 people in this embodiment). Implementation Pattern 1 also included C, which belongs to the lip color category of the color information category. * The input factors were the user's measured values ​​(3 variables) for h and MI belonging to the pigment category of the physiological information category. Specifically, the input factors were the factors belonging to the pigment category of the physiological information category (for example, MI corresponds to this) and the factors belonging to the lip color category of the color information category (for example, C * The input factors were (and h are equivalent), and the output factors were determined from factors belonging to the color type category included in the physiological information category (for example, color group A: pink type, pale type, purple type, and brown type are equivalent). As shown in Figure 10, the generalization performance of this model on the test data was excellent, with an accuracy of 0.88 (88%). Furthermore, the classification evaluation performed by this model also showed the highest percentage of data classified into the desired category. And the user's measured value for this input factor (C *Using a mathematical model (h:40, MI:45), the output factors were determined, and it was found that the ratio of multiple elements belonging to color group A is most likely to belong to the pink type, brown type, pale type, and purple type, in that order. Using this result, for example, when suggesting 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 a suggestion, if a user has a preference (preferred color) for makeup products suitable for brown-type users rather than makeup products suitable for pink-type users, it becomes easier for the user to choose the makeup product suitable for brown-type users, thus enabling appropriate suggestions. Also, in the case of implementation pattern 1, the probability of the user's color type being purple is the lowest, so it is possible to suggest that it is better not to select makeup products suitable for purple-type users. As mentioned above, there are no clear boundaries between lip color types. Therefore, by seeking the most likely color type, as in implementation pattern 1, it becomes possible to make suggestions that are suitable for lip color types without clear boundaries, compared to, for example, seeking only one specific color type and suggesting makeup products and care methods according to that color type. In this way, a mathematical model is used to classify and output multiple elements of a factor belonging to one of the categories based on the input factors (in the case of implementation pattern 1, multiple elements belonging to color group A of the color type category), according to their respective proportions.

[0058] <Implementation Pattern 2> Figure 11 shows an overview of implementation pattern 2. In implementation pattern 2, the proportion of each element belonging to color group A of the color type category—pink type, pale type, purple type, and brown type—was calculated based on a Gaussian naive Bayes model created using measurements from the population (85 people in this embodiment). Implementation pattern 2 also includes L, which belongs to the lip color category of the color information category. * a * , b *, C * The input factors were the user's measured values ​​(8 variables) of h and Age, which belongs to the Age category of the Physiological Information category, and MI and EI, which belong 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 * Using , and h) as input factors, factors belonging to the color type category included in the physiological information category (for example, 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 on the test data was high, with an accuracy of 0.76 (76%). Furthermore, the classification evaluation performed by this model also showed the highest percentage of data classified into the desired category. And this input factor (L * :43, a * :14, b * :15, C *Using a mathematical model and data analysis (with parameters 20, h:40, Age:20, MI:45, EI:73), the output factors were determined to be most likely to belong to the following order: pale type, pink type, brown type, and purple type. Using these results, for example, when suggesting 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, if a user has a preference (preferred color) for makeup products suitable for pink-type users rather than pale-type users, it becomes easier for the user to choose the pink-type makeup product, thus enabling appropriate suggestions. Furthermore, in the case of implementation pattern 2, since there is almost no possibility that the user's color type is purple, it is also possible to suggest that it is better not to select makeup products suitable for purple-type users. As mentioned above, there are no clear boundaries between lip color types. Therefore, by seeking the most likely color type, as in implementation pattern 2, it becomes possible to make suggestions that are suitable for lip color types without clear boundaries, compared to, for example, seeking only one specific color type and suggesting makeup products and care methods according to that color type. In this way, a mathematical model is used to classify and output multiple elements belonging to one of the categories (in the case of implementation pattern 2, multiple elements belonging to color group A of the color type category) based on the input factors, according to their respective proportions.

[0059] <Implementation Pattern 3> Figure 12 shows an overview of implementation pattern 3. In implementation pattern 3, the proportion of each age group belonging to the physiological information category—20s, 30s, 40s, 50s, 60s, and 70s—was calculated based on a Gaussian naive Bayes model created using measurements from the population (85 people in this embodiment). 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 measured values ​​(8 variables) for MBR, Skew, ATI, RI (belonging to the blood flow category of the physiological information category), and MI and EI (belonging to the pigment category). As shown in Figure 12, the generalization performance of this model for the test data was 0.47 (47%). Furthermore, the evaluation of the classification performed by this model showed that the highest percentage of data was classified into the element to be classified. * :44.824, and C * Using the following parameters (21.41, MBR: 1624.2, Skew: 11.8, ATI: 27.3, RI: 0.29, MI: 39.934, EI: 79.575) and a mathematical model to determine the output factors, the proportion of users in their 40s was remarkably high, while the proportions of users in their 30s and 20s were low. Since the actual age of this user is 42, the values ​​of the output factors can be considered highly accurate. Using these results, for example, when suggesting recommended 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, if a user has a preference (preferred color) for makeup products suitable for users in their 30s or 20s rather than those suitable for users in their 40s, it becomes easier for the user to choose the makeup products suitable for users in their 30s or 20s, thus enabling appropriate suggestions. Furthermore, in implementation pattern 3, since the user's age group is unlikely to be in their 50s, 60s, or 70s, it becomes possible to suggest that they should not select makeup products suitable for people in their 50s, 60s, and 70s. In this way, a mathematical model is used to classify and output multiple factors belonging to one of the categories (in the case of implementation pattern 3, multiple elements belonging to the age category) based on the input factors, according to their respective proportions.

[0060] <Implementation Pattern 4> Figure 13 shows an overview of implementation pattern 4. In implementation pattern 4, the age belonging to the age category of the physiological information category was determined based on a multiple regression equation created using measurements from the 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 h 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). In other words, the input factors were factors included in the color type category of the physiological information category (for example, color group A: 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 * Using , and h) as input factors, we obtained factors belonging to the age category, which is a different category from the category to which the input factors belong (for example, Age would be the corresponding factor), as output factors. As shown in Figure 13, the coefficient of determination (R) of this multiple regression equation 2 The correlation coefficient was 0.64, indicating 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 becomes possible to determine the user's age with high accuracy. Furthermore, the factors included in the age category output in implementation pattern 4 shall be limited to age information.

[0061] <Implementation Pattern 5> Figure 14 shows an overview of implementation pattern 5. In implementation pattern 5, the melanin index (MI) belonging to the pigment category of the physiological information category was determined based on a multiple regression equation created using measurements from 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 *and the measured values (4 variables) of Age belonging to the age category of the physiological information category and h were used as input factors. That is, a factor belonging to the age category (for example, corresponding to Age), and a plurality of factors belonging to the lip color category of the color information category (for example, L * C * and h) were used as input factors, and a factor included in the physiological information category (for example, corresponding to MI) was obtained as an output factor. The MI obtained as the output factor belongs to the pigment category of the physiological information category, and the L used as the input factor * C * and h belong to the lip color category of the color information category, and are factors belonging to a category different from the age category of the physiological information category to which Age belongs. The output factor belongs to a category different from the category to which the input factor belongs. Note that the "different category" means that the category to which the input factor belongs and the category to which the output factor belongs are different with respect to the above-described 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 tactile sensation category, lip somatic sensation category, body visual sensation category, body tactile sensation category, body somatic sensation category, lip color category or body color category. As shown in FIG. 14, R 2 by this multiple regression equation was 0.92, and it was clear that there was a correlation. Therefore, it is possible to obtain the MI of the user by inputting the measured values of the user corresponding to the above input factors into the explanatory variables of the multiple regression equation shown in FIG. 14.

[0062] <Embodiment Pattern 6> FIG. 15 shows an outline of Embodiment Pattern 6. In Embodiment Pattern 6, EI belonging to the pigment category of the physiological information category was obtained based on a multiple regression equation created using the measured values of the population (85 people in this embodiment). The variables in the multiple regression equation were selected based on domain knowledge. Implementation Pattern 6 used FAI, which belongs 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: pink type, pale type, purple type, and brown type), and user measurements of height (3 variables) belonging to the physical category of the physiological information category as input factors, and obtained a factor included in the physiological information category (for example, EI) as the output factor. In other words, multiple factors including one or more factors belonging to the physiological information category were used as input factors from the physiological information category and the physical category. Furthermore, EI, which was obtained as an output factor, belongs to the pigment category of the physiological information category and is a factor that belongs to a different category from the blood flow category to which FAI belongs, the color type category to which color group A belongs, and the physical category to which height belongs. As shown in Figure 15, the R of this multiple regression equation 2 The value was 0.57, clearly indicating 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 becomes possible to determine the user's EI.

[0063] As described above, this method allows for the determination of various output factors based on various input factors and mathematical models. As shown in implementation patterns 1 to 3, by determining multiple elements and their ratios, and identifying which elements are most likely, or elements that are less likely but still have a certain probability, it becomes possible to make more appropriate suggestions for makeup products or care methods using the results compared to determining only one element. On the other hand, as shown in implementation patterns 4 to 6, depending on the type of factor, determining only one element may be appropriate. Thus, the input factors and mathematical models should be determined according to the desired output factors and how those output factors will be used. Furthermore, for example, even without user measurements for all the factors shown in Table 2, it is possible to determine predetermined factors as output factors.

[0064] <Lip evaluation system 10> This section describes a lip evaluation system 10 that performs the lip evaluation method described above and evaluates the characteristics of a subject's lips or body using factors different from the input factors as output factors. Figure 16 shows a conceptual diagram of the lip evaluation system 10. The lip evaluation system 10 (hereinafter also referred to as "this system") is an information processing terminal capable of performing 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 in the figures, the lip evaluation system 10 includes an input device such as a keyboard pointing device, a calculation processing unit, a storage unit, a display device, and the like.

[0065] The memory unit 11 is a storage means that stores mathematical models obtained in advance from the population that show the correlation between multiple input factors and output factors. In addition to mathematical models, it also stores programs and data necessary to execute this method. The input unit 12 is an input means for inputting multiple input factors obtained from the subject. This corresponds to an input device provided in an information processing terminal. The calculation unit 13 is a calculation means that determines the output factor based on the mathematical model and the input factor. This corresponds to the arithmetic processing unit provided in the information processing terminal. The output unit 14 is an output means for outputting the calculated output factors. This includes outputting to a display device provided in the information processing terminal, as well as outputting to a device or system different from the lip evaluation system 10, or outputting to a printer. The evaluation unit 15 is an evaluation means that uses output factors to suggest makeup and lip care products, as well as makeup and care methods. This corresponds to the arithmetic processing unit installed in the information processing terminal. Depending on the output factors obtained by the calculation unit 13, it extracts and suggests, for example, a recommended lip cosmetic from among several lip cosmetic products with different color patterns, or extracts and suggests a recommended lip care method from among several lip care methods.

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

[0067] [Table 3]

[0068] Makeup products are intended to enhance the beauty of lip color, but they often add redness to improve facial appearance. In this embodiment, we propose a makeup product that adds redness when applied to bare lips. The pink type has a bright, vibrant lip color, so it doesn't matter what type of makeup product you choose. You can simply suggest that users choose their makeup products according to their preferences. Pale lip colors lack redness, so low-coverage makeup products are not recommended for pale lips, as they will only show the natural lip color without any redness. Purple types have a low-saturation lip color, so using low-saturation or low-coverage makeup products will result in the lip color remaining the same as the natural lip color, i.e., a low-saturation, non-reddish lip color. Therefore, low-saturation and low-coverage makeup products are not recommended. Because brown types have dark lip colors, high-brightness, low-saturation, and low-coverage makeup products will result in the lips remaining the same color as their natural lips, i.e., dark and lacking redness. Therefore, high-brightness, low-saturation, and low-coverage makeup products are not recommended.

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

[0070] [Table 4]

[0071] Generally, a bright red lip color is considered healthy and beautiful. Lips with a bright red color have good blood flow, with blood reaching the extremities, and also contain less melanin pigment. Therefore, in this embodiment, we 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, warm compresses, lip packs, carbonated preparations, and warming preparations. "care target: melanin" refers to care that reduces melanin pigment, and includes melanin-reducing care products, cleansing agents, UV protection preparations, and brightening preparations. For those with a pink skin type, it's best to suggest that they have good blood circulation and low melanin levels, meaning they don't need blood flow or melanin care. However, while they may not need it, preventative blood flow and melanin care is perfectly acceptable. Pale-type eyelids have less melanin pigment, but poor blood circulation makes it difficult for blood to reach the extremities, so blood flow care should be recommended. The purple type has less melanin pigment, but poor blood circulation means blood doesn't reach the extremities, so blood flow care should be recommended. Since brown hair contains a lot of melanin, it's best to recommend melanin pigment care.

[0072] Next, we will explain the differences in suggested makeup products and care methods between when the output factors are determined using the detailed mode and when they are determined using the simplified mode. Table 5 shows the differences in suggested makeup products and skincare methods between the detailed mode and the simplified mode.

[0073] [Table 5]

[0074] In the case of the careful mode shown in Table 5, when suggesting makeup products, if the percentage was 60% or more, the makeup product types shown in Table 3 were recommended; if it was between 30% and 60%, they were partially recommended; and if it was less than 30%, they were not recommended. Partial recommendation means that within that type of makeup product, some colors are recommended and others are not. Furthermore, when suggesting care methods, if the percentage was 60% or more, the care methods shown in Table 4 were strongly recommended; if it was between 30% and 60%, they were recommended; and if it was less than 30%, they were preventatively recommended. As is clear from Table 5, even for the same user, the recommended makeup products and care methods differ depending on whether the request is made in detailed mode or simplified mode. As mentioned above, there are no clear boundaries between lip color types, so rather than specifying one of the multiple elements that make up the output factor, if there are multiple possible color types, it is possible to suggest recommended makeup products and care methods according to the proportion of each of the multiple elements that make up the output factor, thereby providing a wider range of suggestions that are more in line with the lip color. Furthermore, if a recommended care method is implemented based on the output factors determined in the careful mode, and then the output factors are determined again in the careful mode after a predetermined period, even if the type of output factor (color type) remains unchanged, the ratio may change. This change in ratio may also necessitate changes in recommended makeup products and care methods. Thus, by determining the output factors in the careful mode and proposing recommended makeup products and care methods based on their ratios, it becomes possible to provide appropriate suggestions during the process of lip color change (improvement).

[0075] <Variation> In this embodiment, recommended makeup products were suggested based on output factors, but recommended makeup methods could also be suggested based on output factors. Similarly, while recommended skincare methods were suggested based on output factors, recommended skincare products could also be suggested based on output factors.

[0076] In addition to the input factor combinations used in Implementation Pattern 1 and Implementation Pattern 2, it is also possible to determine the probability of each element constituting color group A (pink type, pale type, purple type, and brown type) belonging to the color type category, based on a Gaussian naive Bayes model created using measurements from the population (85 people in this embodiment). Table 6 shows other examples of input factor combinations.

[0077] [Table 6]

[0078] In Table 6, combination 1 corresponds to implementation pattern 2, and combination 9 corresponds to implementation pattern 1. As is clear from Table 6, the generalization performance to the test data is high in all combinations. In addition, combinations 7 and 8 do not use factors belonging to the physiological information category as input factors. Thus, 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 to 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, it is possible to perform more accurate lip evaluation by using factors belonging to the physiological information category as input factors.

[0079] The lip evaluation system may be equipped with a camera that captures images of the user's lips, and input values ​​from the images captured by the camera. This makes it possible to evaluate the lip condition at the time of evaluation. Alternatively, the system may acquire images of the user's lips taken outside the lip evaluation system, and input values ​​from these images. This makes it possible, for example, for the user to send lip images they have taken to the lip evaluation system and perform evaluations 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 an input means, but this is not limited to this. For example, as described above, the values ​​that will become input factors may be measured from an image captured by a shooting device or an acquired image and incorporated into the calculation means, and this incorporation process may also be used as 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 Department

Claims

1. A method for evaluating the characteristics of a subject's lips or body, comprising a group of categories consisting of a physiological information category with factors relating to the physiological characteristics of the subject's lips or body, a sensory information category with factors relating to the sensory characteristics of the subject's lips or body, and a color information category with factors relating to the color information of the subject's lips or body, wherein multiple factors including one or more of the aforementioned factors belonging to the physiological information category are used as input factors, and factors different from the input factors are used as output factors, wherein A lip evaluation method characterized by determining the output factor based on a mathematical model that shows the correlation between the plurality of input factors and the output factor, which is obtained in advance from a population, and the plurality of input factors obtained from the subject.

2. The physiological information categories include a pigment category with lip pigment information as a factor, a blood flow category with lip blood flow information as a factor, a vascular 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 type information as a factor, a body category with the physiological characteristics of the subject's body as a factor, an age category with the subject's age information as a factor, or a gender category with the subject's gender information as a factor. The aforementioned sensory information categories include a lip visual category with lip visual information as a factor, a lip tactile category with lip tactile information as a factor, a lip somatosensory category with lip somatosensory information as a factor, a bodily visual category with body visual information as a factor, a bodily tactile category with body tactile information as a factor, or a bodily somatosensory category with bodily somatosensory information as a factor. The lip evaluation method according to claim 1, characterized in that the color information category includes a lip color category with lip color information as a factor, or a body color category with body color information as a factor.

3. The factors belonging to the physiological information category and the factors belonging to the color information category are used as the input factors. The lip evaluation method according to claim 2, characterized in that a factor belonging to the aforementioned color type category is determined as the output factor.

4. The input factor belongs to any of the following categories: 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, or the body color category. The lip evaluation method according to claim 2 or 3, characterized in that the output factor belongs to a category different from the category to which the input factor belongs.

5. The input factors are defined as a plurality of factors included in the physiological information category and a factor belonging to the color information category. The lip evaluation method according to any one of claims 2 to 4, characterized in that factors belonging to the aforementioned age category are determined as the output factors.

6. The input factors consist of a factor belonging to the age category and a plurality of factors belonging to the color information category. The lip evaluation method according to any one of claims 2 to 5, characterized in that factors belonging to the physiological information category are determined as the output factors.

7. Each of the aforementioned factors is composed of multiple elements that indicate the degree of the factor or classify the factor, The lip evaluation method according to any one of claims 1 to 6, characterized in that, using the mathematical model, each of the multiple elements constituting the output factor is classified and output according to the corresponding ratio based on the input factor.

8. A lip evaluation method according to any one of claims 1 to 7, characterized in that, in accordance with the output factor obtained, a recommended lip cosmetic is extracted from among a plurality of lip cosmetics with different color patterns.

9. The lip evaluation method according to any one of claims 1 to 8, characterized in that, in accordance with the output factor obtained, a recommended lip care method is extracted from among a plurality of lip care methods.

10. A system for evaluating the characteristics of a subject's lips or body, comprising a group of categories consisting of a physiological information category with factors relating to the physiological characteristics of the subject's lips or body, a sensory information category with factors relating to the sensory characteristics of the subject's lips or body, and a color information category with factors relating to the color information of the subject's lips or body, wherein multiple factors including one or more of the aforementioned factors belonging to the physiological information category are used as input factors, and factors different from the input factors are used as output factors, A storage means for storing a mathematical model that shows the correlation between the multiple input factors and the output factors, which is obtained in advance from the population. An input means for inputting a plurality of input factors obtained from the subject, A lip evaluation system characterized by including a calculation means for determining the output factor based on the mathematical model and the input factor.

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