To determine the distribution of beard growth among subjects

A method using a hair-cutting device's movement and parameter measurements to determine beard growth distribution and density addresses the lack of such information in existing technologies, facilitating personalized beard style suggestions.

JP7732005B2Active Publication Date: 2025-09-01KONINKLIJKE PHILIPS NV
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Patent Information

Application Number
JP2023578747
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Priority Date
2021-06-22
Filing Date
2022-06-22
Publication Date
2025-09-01
Estimated Expiration
2042-06-22

Smart Images

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Abstract

According to a first aspect, there is provided a computer-implemented method for determining a beard growth distribution of a subject, the method comprising the steps of receiving (101) movement measurements representative of movement of a hair-cutting device over the subject's face during a hair-cutting process, determining (103) a set of locations of the hair-cutting device during the hair-cutting process from the received movement measurements, analysing (105) the set of locations to determine areas of the face where beard growth is present, and determining (107) the beard growth distribution based on the determined areas of the face where beard growth is present.
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Description

[Technical Field]

[0001] The present disclosure relates to analysis of a hair-cutting process on a subject's face, and in particular to a computer-implemented method, computer program product and apparatus for determining a subject's beard growth distribution from the movement of a hair-cutting device on the subject's face during the hair-cutting process. [Background technology]

[0002] A recent development in the field of hair cutting, particularly facial hair shaving, is a smartphone app that can be used to monitor the use of a hair-cutting device (e.g., an electric shaver), provide advice to the subject on how to obtain better results, and / or provide advice or suggestions for particular facial hair or beard styles to the subject. Beard style suggestions may be based on the subject's face shape category (e.g., wide, long, average, etc.) and beard growth category (e.g., thin, average, thick, etc.), as well as possibly some personal preferences expressed by the subject. These apps may determine the face shape category and beard growth category from a selfie or other image of the subject through an appropriate algorithm. However, using selfies or other images can raise privacy concerns and is technically challenging when the quality of the selfie or other image is poor.

[0003]

[0004] Separately, efforts have been made to improve the monitoring of hair-cutting devices during the hair-cutting process in order to understand the specific movements of the device by the subject. For example, WO2020 / 182698 describes how measurements from a direction sensor in a device for performing a treatment operation on a body part can be processed to determine the location of the device on the body part. WO2016 / 113202 describes estimating the position of a device including head position and movement sensors such as an accelerometer and a gyroscope.

[0004] WO 2019 / 234144 A1 discloses a laser accessory configured to be mechanically attached to a shaving laser to assist a user of the shaving laser. The laser accessory has a camera configured to record images during the shaving process. The laser accessory is communicatively connected to a control unit configured to process image data from the camera to determine at least one physical characteristic of at least one of the user's skin surface and body contours. The laser accessory further includes one or more action sensors for detecting the user's actions, e.g., a sensor for detecting movement. Movement data from the sensors is analyzed by the control unit to provide information about the user's shaving technique, e.g., the number of shaving strokes and the direction and path of the shaving strokes. If the shaving technique is determined to be suboptimal, the user is notified of this. A photograph of the user's face may be shown to the user, showing areas of the face that have been sufficiently shaved or areas that require further shaving.

[0005] U.S. Patent Application Publication No. 2020 / 0226660A1 discloses a digital imaging method that analyzes a digital facial image of a user of a laser device to determine the user's face shape type and the user's ability to grow hair. A facial hair style is suggested based on the determined face shape type and hair growth ability. The user's face shape type and hair growth ability are determined by using a neural network to compare the user's digital facial image with digital facial images of multiple people from a database.

[0006] Thus, while technology is available for monitoring the position or location of a hair-cutting device during the hair-cutting process, existing technology does not provide any information about the distribution of hair (beard) growth on a subject's face, i.e., existing technology does not provide information about the areas of the face where beard growth is present (i.e., the parts of the face where hair is growing), and does not provide information about the density of hair (beard) growth in these areas. This information may be useful, inter alia, for assessing a subject's current beard style and for providing suggestions for different beard styles. Summary of the Invention [Problem to be solved by the invention]

[0007] Therefore, a need exists for a technique for determining the beard growth distribution of a subject. [Means for solving the problem]

[0008] According to a first particular aspect, there is provided a computer-implemented method for determining a beard growth distribution of a subject, the method comprising the steps of receiving movement measurements representative of movement of a hair-cutting device over the subject's face during a hair-cutting process, determining a set of locations of the hair-cutting device during the hair-cutting process from the received movement measurements, analyzing the set of locations to determine areas of the face where beard growth is present, and determining the beard growth distribution based on the determined areas of the face where beard growth is present.

[0009] In some embodiments, determining the beard growth distribution further comprises determining a respective density of beard growth in each determined area of ​​the face based on a respective amount of time spent by the hair-cutting device in each area of ​​the face. The amount of time spent by the hair-cutting device in each area of ​​the face is determined from the temporal information in the location set and the received movement measurements. Thus, the method may provide information about areas where beard growth is present and information about the density of this beard growth.

[0010] In some embodiments, the method further comprises receiving parameter measurements indicative of measurements of one or more parameters related to the hair-cutting process. In these embodiments, the method may comprise analyzing the set of locations and the received parameter measurements to determine areas of the face in which beard growth is present. In these embodiments, the respective densities of beard growth in each determined area of ​​the face may be based on the respective amounts of time spent by the hair-cutting device in each area of ​​the face and the parameter measurements received when the hair-cutting device was in these areas of the face. These embodiments improve the accuracy of the beard growth density information.

[0011] In embodiments in which parameter measurements are received, determining the set of locations may comprise determining candidate locations of the hair-cutting device during the hair-cutting process from the received movement measurements, determining from the received parameter measurements whether the hair-cutting device was cutting hair at the candidate locations, and determining the set of locations of the hair-cutting device during the hair-cutting process by determining a subset of the candidate locations at which the hair-cutting device was cutting hair. These embodiments improve the estimation of locations where beard growth is present by combining information in the movement measurements and information in the parameter measurements.

[0012] The one or more parameters may include any one or more of the current drawn by a motor in the hair-cutting device, the noise or sound produced by the hair-cutting device, and the pressure exerted by the hair-cutting device on the subject's face, which parameters are relatively straightforward to measure in a hair-cutting device and provide a useful indication as to when the hair-cutting device is cutting hair.

[0013] In some embodiments, the method further includes analyzing the set of locations to determine a facial shape of the subject. In these embodiments, analyzing the set of locations to determine a facial shape may include determining the subject's facial shape class as one of a plurality of predetermined facial shape classes. In these embodiments, analyzing the set of locations to determine a facial shape may include, for a plurality of head models corresponding to the plurality of predetermined facial shape classes, mapping the set of locations to a mesh of vertices in the head model corresponding to a particular facial shape class, determining an error metric representing the difference between the mapped locations and the mesh, and determining a facial shape class to which the determined subject's facial shape corresponds as one of the plurality of predetermined facial shape classes based on the determined error metric. In an alternative embodiment, analyzing the set of locations to determine a facial shape may include, for a plurality of head models respectively corresponding to the plurality of predetermined facial shape classes, comparing one or more metrics of a point cloud corresponding to the set of locations to one or more metrics of a respective point cloud corresponding to the head model, and determining a facial shape class to which the subject's facial shape corresponds based on the determined metric.

[0014] In some embodiments, the method further comprises determining a current beard style class of the subject using the determined area of ​​the face where beard growth is present, the current beard style class being determined as one of a plurality of predetermined beard style classes.

[0015] In some embodiments, the method further comprises suggesting a beard style class for the subject based on the determined beard growth distribution, wherein the suggested beard style class is one of a plurality of predetermined beard style classes.

[0016] According to a second aspect, there is provided a computer program product comprising a computer readable medium having computer readable code embodied therein, the computer readable code being configured to, when executed by a suitable computer or processor, cause the computer or processor to perform a method according to the first aspect or any embodiment thereof.

[0017] According to a third aspect, there is provided an apparatus configured to determine a beard growth distribution of a subject, the apparatus being configured to: receive movement measurements representative of movement of a hair-cutting device over the subject's face during a hair-cutting process, determine a set of locations of the hair-cutting device during the hair-cutting process from the received movement measurements, analyze the set of locations to determine areas of the face where beard growth is present, and determine the beard growth distribution based on the determined areas of the face where beard growth is present.

[0018] Apparatus embodiments are also envisaged, in which the apparatus is further configured to operate according to any of the method embodiments according to the first aspect above.

[0019] According to a fourth aspect, there is provided a hair-cutting system, comprising a hair-cutting device and an apparatus according to the third aspect or any embodiment thereof.

[0020] In some embodiments, the apparatus is part of a hair-cutting device. In alternative embodiments, the apparatus is separate from the hair-cutting device.

[0021] These and other aspects will be apparent from and elucidated with reference to the embodiments described hereinafter.

[0022] Exemplary embodiments will now be described, by way of example only, with reference to the following drawings, in which: [Brief explanation of the drawings]

[0023] [Figure 1]1 is a diagram of an exemplary hair-cutting device in the form of a rotary shaver. [Figure 2] FIG. 1 is a block diagram of an exemplary hair-cutting system comprising a hair-cutting device for performing a hair-cutting process according to the present disclosure and an apparatus for determining beard growth distribution; [Figure 3] 1 is a flowchart illustrating an exemplary method according to the present disclosure. [Figure 4] FIG. 10 is a diagram of an exemplary set of locations of a hair-cutting device during a hair-cutting process mapped to a subject. [Figure 5] FIG. 1 illustrates an example set of face shape classes. [Figure 6] FIG. 1 illustrates an example set of beard style classes. DETAILED DESCRIPTION OF THE INVENTION

[0024] As mentioned above, the technology described herein enables the beard growth distribution of a subject to be determined from the location of a hair-cutting device on the subject's face during a hair-cutting process. During the hair-cutting process, the hair-cutting device is moved over the surface of the face (skin), and the hair-cutting device cuts or shaves hair at the location of the hair-cutting device on the face. During the hair-cutting process, measurements representing the movement of the hair-cutting device are obtained. The device may be a handheld device, i.e., a device that is held in the hand of a user. The user of the hair-cutting device may be the person on whom the hair-cutting process is performed (i.e., the user is using the device themselves), or the user of the hair-cutting device may be using the device to perform the hair-cutting process on another person. In either case, the person on whom the hair-cutting process is performed will be referred to herein as the "subject."

[0025] FIG. 1 is a diagram of an exemplary hair-cutting device 2 to which or with which the technology described herein may be applied or used. In FIG. 1, the hair-cutting device 2 is in the form of a rotary shaver, but it will be understood that the technology described herein may be applied to any type of hair-cutting device 2, such as an electric shaver, a foil shaver, a beard trimmer, and a Philips OneBlade. The hair-cutting device 2 comprises a main body 3 held in a user's hand and a cutting head 4 in the form of a shaving portion including a plurality of cutting elements 5 for cutting / shaving hair. Each cutting element 5 comprises one or more circular blades or foils (not shown in FIG. 1 ) that rotate at high speed. When the cutting head 4 is placed on the face and moved, hair on the face is cut by the cutting elements 5. In FIG. 1, the cutting head 4 is illustrated as including three cutting elements 5 arranged in a triangular shape, but it will be understood that the rotary shaver 2 may have a different number of cutting elements 5 and / or different arrangements of the cutting elements 5.

[0026] In Figure 1, various internal components of the hair-cutting device 2 are also illustrated by dashed boxes. Thus, Figure 1 illustrates the hair-cutting device 2 as comprising a movement sensor 6, a motor 7, and two optional sensors 8, 9. The movement sensor 6 is provided for measuring the movement of the hair-cutting device 2 during the hair-cutting process. The motor 7 is provided for generating rotational motion and actuating the cutting element 5 to cut hair, for example by rotating a circular blade or foil. The first optional sensor 8 is a microphone 8 that can be used to measure sounds generated by the motor 7, the cutting head 4, or more generally the hair-cutting device 2 during the hair-cutting process. The second optional sensor 9 is a pressure sensor 9 that can be used to measure pressure exerted by the hair-cutting device 2, and more specifically by the cutting head 4, on the subject's face during the hair-cutting process.

[0027] Figure 2 illustrates a block diagram of an exemplary apparatus 10 for determining a subject's beard growth distribution according to the techniques described herein. The apparatus 10 is illustrated as part of a system 11, which also includes a hair-cutting device 2 (e.g., the rotary shaver illustrated in Figure 1). In the embodiment illustrated in Figure 2, the apparatus 10 is a separate device from the hair-cutting device 2; therefore, the apparatus 10 may be in the form of an electronic device such as a smartphone, smart watch, tablet, personal digital assistant (PDA), laptop, desktop computer, smart mirror, etc. In other embodiments (not shown in Figure 2), the apparatus 10, and in particular the functionality according to the present invention provided by the apparatus 10, is part of the hair-cutting device 2.

[0028] The apparatus 10 comprises a processing unit 12 that provides overall control over the operation of the apparatus 10 and enables the apparatus 10 to implement the methods and techniques described herein. Briefly, the processing unit 12 determines a set of locations of the hair-cutting device 2 during the hair-cutting process from the received movement measurements, analyzes the set of locations to determine areas of the face where beard growth is present, and determines a beard growth distribution based on the determined areas of the face where beard growth is present.

[0029] Processing unit 12 may be configured to receive movement measurements from other components of device 10, and therefore processing unit 12 may include or comprise one or more input ports or other components for receiving movement measurements from other components. Processing unit 12 may also include or comprise one or more output ports or other components for communicating with other components of device 10.

[0030] Processing unit 12 can be implemented in many ways using software and / or hardware to perform the various functions described herein. Processing unit 12 comprises one or more microprocessors or digital signal processors (DSPs) programmed using software or computer program code to perform the required functions and / or to control components of processing unit 12 to perform the required functions. Processing unit 12 is implemented as a combination of dedicated hardware that performs some functions (e.g., amplifiers, pre-amplifiers, analog-to-digital converters (ADCs) and / or digital-to-analog converters (DACs)) and processors (e.g., one or more programmed microprocessors, controllers, DSPs, and associated circuitry) that perform other functions. Examples of components used in various embodiments of the present disclosure include, but are not limited to, conventional microprocessors, DSPs, application-specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs).

[0031] Processing unit 12 may include or be associated with a memory unit 14. Memory unit 14 may store data, information, and / or signals (including movement measurements, any results of processing of the movement measurements, or any intermediate results) for use by processing unit 12 in controlling the operation of device 10 and / or in executing or implementing the methods described herein. In some embodiments, memory unit 14 stores computer-readable code that may be executed by processing unit 12 to cause processing unit 12 to perform one or more functions, including the methods described herein. In particular embodiments, the program code may be in the form of an application for a smartphone, tablet, laptop, or computer. The memory unit 14 may comprise any type of non-transitory machine-readable medium, such as cache or system memory, including volatile and non-volatile computer memory such as random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), read only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), and electrically erasable PROM (EEPROM®), and the memory unit may be implemented in the form of a memory chip, an optical disk (such as a compact disk (CD), digital versatile disk (DVD) or Blu-Ray disk), a hard disk, a tape storage solution, or a solid-state device, including a memory stick, a solid-state drive (SSD), a memory card, etc.

[0032] 2, the apparatus 10 is separate from the hair-cutting device 2, and therefore the apparatus 10 also includes an interface circuit 16 that enables the apparatus 10 to receive movement measurements from the movement sensor 6 in the hair-cutting device 2. The interface circuit 16 in the apparatus 10 enables data connection and / or data exchange with other devices, such as any one or more of the hair-cutting device 2, a server, a database, a user device, a sensor. The connection with the hair-cutting device 2 (or any other device) may be direct or indirect (e.g., via the internet), and thus the interface circuit 16 may enable connection between the apparatus 10 and a network, or may enable connection between the apparatus 10 and other devices (such as the hair-cutting device 2) directly via any desired wired or wireless communication protocol. For example, interface circuit 16 may operate using WiFi, Bluetooth, Zigbee, or any cellular communication protocol (including, but not limited to, Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE), LTE-Advanced, etc.). In the case of a wireless connection, interface circuit 16 (and thus device 10) includes one or more suitable antennas for transmitting / receiving over a transmission medium (e.g., air). Alternatively, in the case of a wireless connection, interface circuit 16 includes means (e.g., connectors or plugs) that allow interface circuit 16 to be connected to one or more suitable antennas external to device 10 for transmitting / receiving over a transmission medium (e.g., air). Interface circuit 16 is connected to processing unit 12.

[0033] 2, device 10 includes one or more user interface components, including one or more components that enable a user of device 10 to input information, data, and / or commands into device 10 and / or enable device 10 to output information or data, such as information indicative of a determined beard growth profile and, in some embodiments, beard style suggestions, to a user of device 10. The user interface may include any suitable input component, such as, but not limited to, a keyboard, a keypad, one or more buttons, switches, or dials, a mouse, a trackpad, a touch screen, a stylus, a camera, a microphone, etc., and the user interface may include any suitable output component, such as, but not limited to, a display unit or display screen, one or more lights or light elements, one or more loudspeakers, a vibration element, etc.

[0034] It will be understood that practical implementations of device 10 will include additional components to those illustrated in Figure 2. For example, device 10 may also include a power source, such as a battery, or components that allow device 10 to be connected to a mains power source.

[0035] The hair-cutting device 2 illustrated in Figure 2 includes a movement sensor 6 for measuring the movement of the hair-cutting device 2 during the hair-cutting process. The hair-cutting device 2 also comprises a device processing unit 24 and an interface circuit 26. The interface circuit 26 is for transmitting signals from the hair-cutting device 2 to the apparatus 10, such as transmitting movement measurements. The interface circuit 26 may be implemented according to any of the options outlined above for the interface circuit 16 in the apparatus 10, in order to communicate with the interface circuit 16 in the apparatus 10.

[0036] The movement sensor 6 is integrated with or otherwise fixed to the hair-cutting device 2 such that the movement sensor 6 directly measures the movement of the hair-cutting device 2. The movement sensor 6 may output movement measurements in the form of a continuous signal(s) or in the form of a time series of measurement samples at the sampling rate of the movement sensor 6. In some embodiments, the movement sensor 6 is, for example, an acceleration sensor that measures acceleration along three orthogonal axes (i.e., in three dimensions). Alternatively or additionally, the movement sensor 6 may comprise a gyroscope and / or a magnetometer. In some embodiments, multiple types of movement sensors 6 may be part of an inertial measurement unit (IMU). For example, the IMU may comprise an accelerometer, a gyroscope, and a magnetometer.

[0037] The device processing unit 24 overall controls the operation of the hair-cutting device 2, e.g. the activation and deactivation of the motor 7 and thus the cutting elements 5 in the cutting head 4, in order to carry out the hair-cutting process. The device processing unit 24 may be realised in many ways according to any of the options outlined above for the processing unit 12 in the apparatus 10.

[0038] The device processing unit 24 may be connected to the movement sensor 6 and receive measurements of movement of the hair-cutting device 2 from the movement sensor 6, for example via an input port to the device processing unit 24. In some embodiments, the device processing unit 24 outputs the measurements (e.g. raw movement measurements) to the interface circuit 26 for transmission to the apparatus 10 for subsequent processing. In alternative embodiments, the device processing unit 24 may perform some initial processing on the measurements, for example to reduce noise or other artifacts, and the device processing unit 24 outputs processed movement measurements to the interface circuit 26 for transmission to the apparatus 10 for subsequent processing.

[0039] In embodiments in which the hair-cutting device 2 comprises a microphone 8, the device processing unit 24 may be connected to the microphone 8 to receive audio measurements. The microphone 8 is located on the hair-cutting device 2 to measure audio generated by the motor 7, the cutting head 4, or more generally the hair-cutting device 2 during the hair-cutting process. The microphone 8 may output audio measurements in the form of a continuous signal(s) or in the form of a time-series of measurement samples according to the sampling rate of the microphone 8.

[0040] In embodiments in which the hair-cutting device 2 comprises a pressure sensor 9, the device processing unit 24 may be connected to the pressure sensor 9 to receive a measurement of the pressure exerted by the subject's face on the cutting head 4 (which is equivalent to the pressure exerted by the cutting head 4 on the subject's face). The pressure sensor 9 is disposed on the hair-cutting device 2 to measure the exerted pressure. For example, the pressure sensor 9 may be positioned below one or more of the cutting elements 5, or between the body 3 and the cutting head 4. The pressure sensor 9 may output pressure measurements in the form of a continuous signal(s) or in the form of a time series of measurement samples according to the sampling rate of the pressure sensor 9.

[0041] In embodiments where the apparatus 10 or the functionality of the apparatus 10 is part of the hair-cutting device 2, the device processing unit 24 may perform the functionality of the apparatus processing unit 12 to determine the subject's beard growth distribution.

[0042] It will be appreciated that practical implementations of the hair-cutting device 2 will include additional components to those illustrated in Figure 2. For example, the hair-cutting device 2 may also include a power source such as a battery or a component that allows the hair-cutting device 2 to be connected to a mains power source.

[0043] 3 illustrates an exemplary method performed by device 10 in accordance with the techniques described herein. One or more of the method steps may be performed by processing unit 12 in device 10, in conjunction with interface circuitry 16 (if present) and memory unit 14, as appropriate. Processing unit 12 performs one or more steps in response to execution of computer program code, which may be stored in a computer-readable medium, such as memory unit 14.

[0044] As mentioned above, the technique described herein provides a set of locations of the hair-cutting device 2 during the hair-cutting process to be determined from the received movement measurements. Thus, in step 101, movement measurements representative of the movement of the hair-cutting device 2 on the subject's face during the hair-cutting process are received. The movement measurements may be received from one or more movement sensors 6. In the following, it is assumed that the movement sensor 6 is an accelerometer, but other and / or additional types of movement sensors may be used. The set of locations is analyzed to determine areas of the face where beard growth is present, and a beard growth distribution is determined based on the areas of the face where beard growth is present.

[0045] In step 103, the movement measurements from the movement sensor 6 are processed to determine the location of the hair-cutting device 2 during the hair-cutting process (e.g., step 103 determines the location where the user shaved). In embodiments where the movement sensor 6 is an accelerometer, step 103 may involve double-integrating the acceleration measurements with respect to time to determine the location. Preferably, step 103 is performed when the hair-cutting process (e.g., shaving) is completed, so that all movement measurements are available for analysis. In certain embodiments, the movement measurements may be used to determine the time sequence of locations of the hair-cutting device 2 during the hair-cutting process. These locations may be represented by Cartesian coordinates (i.e., X, Y, Z coordinates), although other coordinate systems may alternatively be used. In some embodiments, step 103 may be implemented using the techniques described in WO2020 / 182698. FIG. 4 is a diagram of an exemplary set of locations of the hair-cutting device 2 during the hair-cutting process mapped onto an image of a subject. Each location of the hair-cutting device 2 is represented as a dot.

[0046] In some embodiments of step 103, the set of locations determined from the movement measurements is filtered to remove any locations where the hair-cutting device 2 is not cutting / shaving hair. In these embodiments, in step 103, the movement measurements from the movement sensor 6 are processed to determine candidate locations for the hair-cutting device 2, and a subset of the candidate locations is selected as the set of locations for the hair-cutting device 2 during the hair-cutting process. For example, the candidate locations include locations where the hair-cutting device 2 is not in contact with the face, e.g., at the start and end of the hair-cutting process and during the hair-cutting process if the hair-cutting device 2 is repositioned to another part of the face, and these candidate locations are not useful for determining the subject's facial shape or areas of the face where beard growth is present. These candidate locations where no hair cutting or shaving has occurred may be excluded from the set of locations, and the remaining candidate locations are therefore locations where hair cutting or shaving has occurred.

[0047] In these embodiments, measurements of one or more parameters related to the hair-cutting process may be analyzed to determine whether hair cutting has occurred. The one or more parameters may be measured during the hair-cutting process, the measurements may be synchronized with the movement measurements, and the parameter measurements may be used to determine whether hair cutting has occurred at various candidate locations of the hair-cutting device 2. The one or more parameters may include any of the current drawn by the motor 7 in the hair-cutting device 2, the noise or sound generated by the hair-cutting device 2, and the pressure exerted by the hair-cutting device 2 on the subject's face.

[0048] The measurement of the current drawn by the motor 7 may be output from the motor 7 itself, or may be measured by the device processing unit 24 in the hair-cutting device 2. When hair cutting is occurring, the current drawn by the motor 7 is higher than when hair is not cut. Therefore, the current drawn by the motor 7 may be compared to a threshold value to determine whether hair is being cut. If hair is not cut at a candidate location, this candidate location is eliminated. Measurements of the noise or sound generated by the hair-cutting device 2 may be obtained using the microphone 8 in the hair-cutting device 2. When hair cutting is occurring, the noise or sound generated by the hair-cutting device 2, and mainly the motor 7 and cutting element 5, is different from when hair is not being cut. Therefore, measurements of the noise or sound generated by the hair-cutting device 2 may be analyzed to determine whether the noise or sound corresponds to hair being cut. In some embodiments, the analysis of the noise or sound may evaluate the amplitude or maximum amplitude of the measured noise or sound. Additionally or alternatively, the analysis of the noise or sound may evaluate the frequency content of the noise or sound. If it is determined that the hair has not been cut at a particular candidate location, then that candidate location is eliminated.

[0049] Measurements of the pressure exerted by the hair-cutting device 2 on the subject's face may be obtained using the pressure sensor 9. When hair cutting is occurring, the hair-cutting device 2 is pressed against the subject's face. Thus, the measured pressure may be analyzed to determine whether the hair-cutting device 2 is pressed against the face at a particular candidate location. Candidate locations where the hair-cutting device 2 is not pressed against the face may be eliminated.

[0050] In the example illustrated in Figure 4, the lighter colored dots correspond to candidate locations where the pressure measurements indicate that hair cutting or shaving has occurred, and the darker colored dots correspond to candidate locations where the pressure measurements indicate that hair cutting or shaving has not occurred. The darker colored dots are then removed from the location set.

[0051] In some embodiments, filtering of candidate locations may also be used to remove outliers from the set of locations, for example, due to measurement errors or artifacts. For example, one or more candidate locations may appear to be outliers when compared to the rest of the candidate locations, and these outliers may be excluded. In the example illustrated in FIG. 4, a group of locations above the forehead may be identified as an outlier when compared to the rest of the candidate locations, and this group of locations above the forehead may be excluded. In another example, if a particular candidate location suggests that the hair-cutting device 2 is following a path that is inconsistent with the shape of the face, this candidate location may be excluded as an outlier. In embodiments in which the face shape is determined using the techniques described below, these outlier locations may be identified based on the distance between this location and the nearest vertex in the head model being too large (i.e., above a threshold).

[0052] In some embodiments, the set of locations determined in step 103 may be used to determine the shape of the subject's face. In practice, for a subject with a "long face" shape, the hair-cutting device 2 is moved more in the vertical direction (compared to a subject with a round face), resulting in more vertical acceleration being detected by the movement sensor 6. Similarly, for a subject with a wide face, the hair-cutting device 2 is moved more in the horizontal direction. As a result, the locations for a subject with a long face will show a vertically elongated pattern, and the locations for a subject with a wide face will show a horizontally elongated pattern.

[0053] Typically, a subject's face (or, more generally, a subject's head) can be classified into one of several different face shape classes. FIG. 5 illustrates an exemplary set of six face shape classes. The face shape classes in FIG. 5 include long faces, round faces, oval faces, square faces, heart faces, and diamond faces. Those skilled in the art will understand that other or additional face shape classes may be included, or that subclasses may be defined for one or more of the classes illustrated in FIG. 5 . For example, tapered square, narrow diamond, wide diamond, etc. In addition, while the face shape classes illustrated in FIG. 5 relate to the shape of the face as viewed from the front, the face shape classes may also differ based on the side contours of the face, as the hair-cutting device 2 is typically also used on the sides of the face and part of the neck. For example, for each of the six face shape classes illustrated in FIG. 5 , there may be subclasses of "shallow," "normal," and "long" that relate to the depth of the face (e.g., the distance from the back of the chin to the front). As another example, for each of the six face shape classes illustrated in FIG. 5, there may be subclasses for various jaw contours, such as short chin, long chin, double chin, protruding chin, pointed chin, receding chin, etc.

[0054] In a first embodiment for determining face shapes, for each face shape class to be distinguished, a set of locations is mapped to a typical 3D head model. In particular, for a particular 3D head model formed as a mesh of vertices, each location of the hair-cutting device 2 may be mapped or projected onto the mesh, and the corresponding distance between the location and the mesh may be calculated. For example, the Euclidean distance between the location and the vertices of the head model may be calculated, and the smallest distance may be selected as the distance to the mesh. Then, an error metric representing the mapping of the location to the head model may be calculated. This error metric may be calculated based on the distance between the location and each nearest vertex in the head model. For example, the error metric may be calculated as the average (mean) or median of the distance between the location and each nearest vertex. This mapping and error metric calculation may be repeated for head models representing different face shapes, and the face shape associated with the head model with the smallest error metric may be selected as the face shape of the subject.

[0055] In a second embodiment for determining face shape, a "point cloud" corresponding to a set of locations in 3D space is compared with a point cloud of 3D head models representing different face shapes to identify the head model that most closely resembles the "point cloud" of locations. In particular, one or more metrics of the point cloud may be determined and compared with corresponding metrics of the different head models. The one or more metrics of the point cloud and head model may be, for example, the width of the face represented by the point cloud or model, the length of the face represented by the point cloud or model, the ratio of face width to face length, etc. The head model having the metric that is most similar to the metric of the point cloud may be determined as representing the subject's face shape. When multiple metrics are used, the metrics may be weighted to determine the most similar head model from the possible head models.

[0056] In step 105, the location set determined in step 103 is analyzed to determine areas of the subject's face where beard growth exists. Typically, facial areas that do not have hair or no hair growth do not need to be shaved, and therefore these facial areas will be rarely present in the location set of the hair-cutting device 2 during the hair-cutting process. Areas with a lot of hair growth need more attention from the hair-cutting device 2 and will usually be visited more frequently during the hair-cutting process. It should be noted that the areas of the subject's face where beard growth exists are areas where hair grows on the subject. That is, even following the hair-cutting process, the subject's face may already be clean-shaven, and the areas of beard growth are areas of the face where the hair-cutting device 2 has cut the hair, resulting in a clean shaven look. Similarly, one or more areas of the subject's face may still have hair following the hair-cutting process (e.g., the hair in these areas has been trimmed rather than completely shaved), and these areas are also areas of beard growth.

[0057] Thus, in embodiments where the set of locations excludes locations where the hair-cutting device 2 has not cut hair, the set of locations of the hair-cutting device 2 may be considered to represent areas of the face where beard growth is present.

[0058] In embodiments where measurements of one or more parameters are available (whether or not these measurements are used to filter the set of candidate locations in step 103), these parameter measurements may be analyzed to determine when the hair-cutting device 2 was cutting hair, and the area of ​​beard growth may be determined as the location corresponding to when the parameter measurements indicated that the hair-cutting device 2 was cutting hair.

[0059] In step 107, a beard growth distribution is determined for the subject based on the areas identified as having beard growth in step 105. The beard growth distribution is a representation of the subject's face that indicates which parts of one or more parts of the face have beard growth present, i.e., which parts or parts of the face have hair growth.

[0060] In some embodiments of step 107, the locations determined in step 105 to have hair growth may be mapped to a 3D head model to associate these locations with vertices of a mesh network representing the 3D head model. In embodiments in which the subject's facial shape is determined, the 3D head model onto which the hair growth areas are mapped may be a 3D head model that corresponds to the subject's facial shape. Alternatively, the 3D head model onto which the hair growth areas are mapped may be a common or generic head model.

[0061] In some embodiments, information about the distribution of beard growth may be output to the subject or other user of the hair-cutting device 2 or apparatus 10. This information may be output in the form of an image showing areas of the face where hair growth is present. The output image may be an image (e.g., a selfie or other photograph) of the subject with the areas of beard growth indicated or superimposed. Alternatively, the output image may be a generic image of the face or head with the areas of beard growth indicated or superimposed.

[0062] In some embodiments of step 107, the beard growth distribution may further be based on the density of beard growth in the areas of the face where hair growth is present (i.e., it includes information about density). Thus, in addition to the beard growth distribution indicating the areas of the face where hair is growing, the beard growth distribution may also indicate the density or thickness of that hair growth. It should be noted that while the density of hair growth primarily refers to the number of hair follicles from which hair grows in a particular facial area, density may also or alternatively relate to the thickness of individual hairs in a particular area.

[0063] Thus, some embodiments of step 107 further comprise determining the density of hair growth in the area of ​​the face where hair growth is present. The density of hair growth can be approximated from the amount of time the hair-cutting device 2 spends cutting hair in that area. That is, an area with a low density of hair growth will typically require the hair-cutting device 2 to make fewer "passes" over that area and / or spend less time in that area than an area with a high density of hair growth. The amount of time the hair-cutting device 2 spent in a particular area can be determined from the temporal information associated with the location set and the movement measurements. That is, the temporal (time) information is received as part of the movement measurements, and thus a time can be associated with each determined location of the hair-cutting device 2 during the hair-cutting process. By evaluating the distribution of the locations of the hair-cutting device 2 during the hair-cutting process, the amount of time (or relative amounts of time) that the hair-cutting device 2 spent in different areas of the face can be determined. As stated, areas of the face where the hair-cutting device 2 spent a relatively long amount of time may be considered to be areas with a higher density of hair growth, and areas of the face where the hair-cutting device 2 spent a relatively short amount of time may be considered to be areas with a lower density of hair growth. In a simple embodiment, a measure of the density of hair growth in an area may be given by the time spent in that area divided by the duration of the hair-cutting process (i.e., the total shaving time).

[0064] In some embodiments, in addition to considering the time spent cutting hair in each area, the density of hair growth may be determined based on measurements of one or more parameters. In areas with denser beard growth, the motor 7 of the hair-cutting device 2 will have to work harder than in areas with less dense beard growth, and therefore the current drawn by the motor 7 will be higher in areas with denser hair growth than in areas with less dense hair growth. Thus, in some embodiments, the current drawn by the motor 7 while the hair-cutting device 2 is in a particular location may be evaluated and used to provide an indication of the density of beard growth at that location. For example, the current drawn by the motor 7 may be compared to one or more threshold values ​​to determine the density of beard growth at that location.

[0065] In a further embodiment, the current drawn by the motor 7 may be determined upon a first visit to a particular area of ​​the face (the first visit being determined from the temporal information associated with the determined location), and this current may indicate the density of beard growth in that area before the start of the hair-cutting process. When the same area is visited multiple times by the hair-cutting device 2 and the current drawn by the motor 7 remains high, this indicates high levels of beard growth. Alternatively, if the current drawn by the motor 7 upon subsequent visits to the area during the same hair-cutting process is lower or very low, this most likely means that the subject is not entirely satisfied with the cleanness of the shave, but this does not necessarily indicate high levels of beard growth in this area. Thus, to estimate the density of beard growth each time the hair-cutting device 2 is over a particular area x, the visit duration d i and their visit i The average motor current during the test is calculated. The whisker growth density is calculated as, for example, d i and c i For example, the weighted average can be

number

[0066] Additionally or alternatively, the noise or sound generated by the hair-cutting device 2 in areas with denser beard growth may differ from the noise or sound generated in areas with less denser beard growth. Thus, in some embodiments, measurements of the noise or sound generated by the hair-cutting device 2 at a particular location, or changes in the generated noise or sound relative to another location, may be evaluated and used to provide an indication of the density of beard growth at that location. For example, the measurements of the noise or sound may be compared to one or more threshold values ​​to determine the density of beard growth at that location.

[0067] In some embodiments, the method may further comprise determining a current beard style class based on the beard growth distribution determined in step 107. That is, a number of beard style classes may be predefined, and the beard growth distribution is used to determine which of the beard style classes the subject has before and / or after the hair-cutting process. Figure 6 illustrates an exemplary set of beard style classes, from which the subject's current beard style may be determined. Thus, Figure 6 illustrates 23 different beard style classes, including various combinations and / or styles of beards and moustache, as well as a "clean-shaven" style.

[0068] For example, the area of ​​hair growth indicated by the beard growth distribution may be compared to the area of ​​hair growth in each beard style class to find the best match, and that beard style class may be selected as the subject's current beard style class. Alternatively, the user or subject may be suggested beard style classes via a graphical user interface on device 10, and the user or subject may manually select the correct beard style class.

[0069] In some embodiments, the method may further comprise determining and providing a beard style class suggestion for the subject. The suggestion may be determined based on information on beard growth distribution for areas of the face where hair is growing. In some embodiments, the suggested beard style class is determined from beard style classes in which the subject has required beard growth. Thus, a pattern of areas in which the subject has hair growth can be matched with areas of required beard growth for each of the beard style classes.

[0070] By way of example, if it is determined that a subject has only slight beard growth on their upper lip, but full beard growth elsewhere, the suggested beard style class may be any of the beard style classes that do not require a mustache, for example, a "chin strap" beard class style.

[0071] In some embodiments, the subject's current beard style class may be taken into consideration when determining the suggested beard style class. In particular, the suggested beard style class is a beard style that can be achieved from the subject's current beard style class. For example, if the subject's current beard style class is the "Van Dyke" style class illustrated in FIG. 6, then the suggested beard style class may be selected from "Original Goatee," "Soul Patch," "Natural Mustache," and "Zappa."

[0072] In embodiments in which the subject's face shape is determined, the suggested beard style class for the subject may be determined taking into account the subject's face shape or the subject's face shape class. For example, a particular beard style class may only be suitable for a particular face shape class / shape, in which case the suggested beard style class may be selected from those that are suitable for the subject's face shape class / shape.

[0073] In some embodiments, the beard style class suggestions may take into account one or more preferences of the subject, which may be input via a user interface of device 10. The preferences may indicate, for example, whether the subject desires or does not desire a mustache, or whether they desire or do not desire an area of ​​stubble.

[0074] Thus, a technique is provided for determining a subject's beard growth distribution.

[0075] Variations to the disclosed embodiments can be understood and effected by those skilled in the art, from a study of the drawings, the disclosure, and the appended claims, in practicing the principles and techniques described herein. In the claims, the words "comprise," "include," and "have" do not exclude other elements or steps, and the words "a" and "an" do not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain means are recited in mutually different dependent claims does not indicate that a combination of these means cannot be used to advantage. A computer program may be stored or distributed on a suitable medium, such as an optical storage medium or a solid-state medium, supplied together with or as part of other hardware, or in other forms, such as via the Internet or other wired or wireless telecommunications systems. Any reference signs in the claims should not be construed as limiting the scope.

Claims

1. 1. A computer-implemented method for determining a beard growth distribution of a subject, the method comprising: receiving movement measurements representative of movement of a hair-cutting device over the subject's face during a hair-cutting process; determining a location set from the received movement measurements, the location set being a set of locations visited by the hair-cutting device during the hair-cutting process; analyzing the set of locations to determine areas of the face where beard growth is present; determining the beard growth distribution based on the determined area of ​​the face where beard growth is present; 10. A method comprising:

2. 2. The method of claim 1, wherein determining the beard growth distribution further comprises determining a respective density of the beard growth in each determined area of ​​the face based on a respective amount of time spent by the hair-cutting device in each area of ​​the face, wherein the amount of time spent by the hair-cutting device in each area of ​​the face is determined from temporal information in the location set and the received movement measurements.

3. The method of claim 1 or 2, wherein the method further comprises receiving parameter measurements indicative of measurements of one or more parameters related to the hair-cutting process.

4. The method of claim 3 , further comprising analyzing the set of locations and the received parameter measurements to determine the areas of the face where beard growth is present.

5. 4. A method according to claim 3 dependent on claim 2, wherein the respective densities of the beard growth in the determined areas of the face are based on the respective amounts of time spent by the hair-cutting device in the areas of the face and the parameter measurements received when the hair-cutting device was in these areas of the face.

6. 4. The method of claim 3, wherein the one or more parameters include any one or more of the current drawn by a motor in the hair-cutting device, the noise or sound produced by the hair-cutting device, and the pressure exerted by the hair-cutting device on the face of the subject.

7. The method of claim 1 , further comprising analyzing the set of locations to determine the shape of the subject's face.

8. The method of claim 7 , wherein analyzing the set of locations to determine the face shape comprises determining the subject's face shape class as one of a plurality of predetermined face shape classes.

9. The step of analyzing the set of locations to determine the face shape comprises: for a plurality of head models corresponding to the plurality of predetermined face shape classes: mapping the set of locations to a mesh of vertices in a head model corresponding to a particular face shape class; determining an error metric representing the difference between the mapped location and the mesh; determining, based on the determined error metric, one of the plurality of predetermined face shape classes to which the determined shape of the subject's face corresponds; and 9. The method of claim 8, comprising:

10. Analyzing the set of locations to determine the facial shape comprises: comparing, for a plurality of head models respectively corresponding to the plurality of predetermined face shape classes, one or more metrics of a point cloud corresponding to the set of locations with one or more metrics of a respective point cloud corresponding to the head model; determining the face shape class to which the shape of the subject's face corresponds based on the determined metric; 9. The method of claim 8, comprising:

11. 2. The method of claim 1, further comprising: determining a current beard style class of the subject using the determined area of ​​the face where beard growth is present, wherein the current beard style class is determined as one of a plurality of predetermined beard style classes.

12. 2. The method of claim 1, further comprising: suggesting a beard style class for the subject based on the determined beard growth distribution, wherein the suggested beard style class is one of a plurality of predetermined beard style classes.

13. 10. A computer readable medium having computer readable code embodied therein, said computer readable code, when executed by a suitable computer or processor, causing said computer or processor to perform the method of claim 1.

14. 1. An apparatus for determining beard growth distribution of a subject, said apparatus comprising: receiving movement measurements representative of movement of a hair-cutting device over the subject's face during a hair-cutting process; determining a location set from the received movement measurements, the location set being a set of locations visited by the hair-cutting device during the hair-cutting process; analyzing the set of locations to determine areas of the face where beard growth is present; determining the beard growth distribution based on the determined area of ​​the face where beard growth is present; and An apparatus for performing the above.

15. A hair cutting device; The device according to claim 14; A hair cutting system comprising:

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