Abstract: According to an aspect, there is provided a computer-implemented method for providing visual feedback to a user of a rotary shaver. The method comprises (i) receiving movement measurements representing movement of the rotary shaver during a shaving operation; (ii) processing the received movement measurements to determine a representation of a trajectory of movement of the rotary shaver during the shaving operation; (iii) processing the determined representation to project the representation onto a two-dimensional plane; (iv) generating a graphical user interface, GUI, the GUI including the projected representation and a graphical template comprising an annular target zone for a correct circular motion of the rotary shaver during the shaving operation; and (v) displaying the generated GUI using a display unit.

Abstract: The invention relates to a portable device (1100) comprising a bottom surface (BS) intended to be in contact with a textile (TXT). The portable device comprises an image sensor (5) for taking an image of a textile, and an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8a) for executing an algorithm stored in the portable device, using the taken image as an input of said algorithm, to obtain a classification of the textile. The image sensor and the control unit are integrated within the portable device. The image sensor has an active surface sensitive to light, which is oriented compared to said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees; and/or the illumination system (6) has a light source oriented compared to the said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees.

Abstract: A computer-implemented method for estimating surface area and/or volume of a subject's body or body part. First, at least one image, including the subject's face, is obtained. The image is processed to determine facial image parameter(s) of the subject's face. The subject's characteristic(s) including age, weight, height, and/or gender—is/are also determined. A facial parametric model and the facial image parameters are used to determine facial shape parameters of the subject's face, where the facial parametric model relates specific values for facial image parameters to a respective 3D representation of a face having respective values for the facial shape parameters. A prediction model with the characteristic(s) and the facial shape parameters are used to predict a 3D representation of the subject's full body. The predicted 3D representation of the subject's full body is analyzed to estimate the surface area and/or volume of the subject's body or body part.

Abstract: According to an aspect, there is provided a computer-implemented method for providing visual feedback to a user of a rotary shaver. The method comprises (i) receiving movement measurements representing movement of the rotary shaver during a shaving operation; (ii) processing the received movement measurements to determine a representation of a trajectory of movement of the rotary shaver during the shaving operation; (iii) processing the determined representation to project the representation onto a two-dimensional plane; (iv) generating a graphical user interface, GUI, the GUI including the projected representation and a graphical template comprising an annular target zone for a correct circular motion of the rotary shaver during the shaving operation; and (v) displaying the generated GUI using a display unit.

Abstract: A portable textile treatment device includes a heatable soleplate for contacting and treating the textile, an image sensor and an illumination system. The image sensor has an active surface sensitive and takes an image of the textile, and the illumination system has a light source that illuminates a portion of the textile when the image is being taken. The portable device also includes a control unit configured to execute an algorithm stored in the portable device for obtaining a classification of the textile based on taken image, and based on the classification for controlling at least one operating parameter of the portable textile treatment device. The image sensor and/or light source are oriented with respect to the surface of the heatable soleplate, with an absolute value of an orientation angle being in the range from 15 to 70° C.

Abstract: The invention relates to a method of operating a textile treatment device comprising a heatable soleplate intended to be in contact with a textile for treating the textile. The method comprises a first step (1001) of setting a first temperature target for the heatable soleplate, and a step (1002) of detecting movement of said textile treatment device. If the step (1002) of 5 detecting movement did not detect any movement of said textile treatment device during more than a given first time duration, a step (1004) of actively decreasing the temperature of the heatable soleplate (4) up to reaching a first given temperature having a value below said first temperature target.

Abstract: The invention relates to a portable textile treatment device (1) comprising a heatable sole plate (4) intended to be in contact with a textile (TXT) for treating the textile. The portable textile treatment device also comprises an image sensor (5) for taking an image of the textile to be treated, an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8) configured for executing an algorithm stored in said portable textile treatment device, using the taken image as an input of said algorithm, to obtain a classification of the textile; and controlling, based on said classification, at least one operating parameter of the portable textile treatment device. The image sensor and the control unit are integrated within the portable textile treatment device.

Abstract: A system and method are provided which use a machine learning algorithm to obtain a learned annotation of objects in one or more scales of a multiscale image. A viewing window (300) is provided for viewing the multiscale image. The viewing window is configurable on the basis of a magnification factor, which selects one of the plurality of scales for viewing, and a spatial offset parameter. A user may provide a manual annotation of an object in the viewing window, which is then used as training feedback in the learning of the machine learning algorithm. To enable the user to more effectively provide the manual annotation, the magnification factor and the spatial offset parameter for the viewing window may be automatically determined, namely by the system and method determining where in the multiscale image the manual annotation of the object would have sufficient influence on the learned annotation provided by the machine learning algorithm.

Abstract: A method of assisting in selection of a particular mask from among a plurality of masks, the method comprising: generating a plurality of augmented faces, each augmented face corresponding to a respective mask of the plurality of masks; and associating each augmented face with a respective mask of the plurality of masks.

Abstract: The invention relates to a method of operating a textile treatment device comprising a heatable soleplate intended to be in contact with a textile for treating the textile. The method comprises a first step (1001) of setting a first temperature target for the heatable soleplate, and a step (1002) of detecting movement of said textile treatment device. If the step (1002) of 5 detecting movement did not detect any movement of said textile treatment device during more than a given first time duration, a step (1004) of actively decreasing the temperature of the heatable soleplate (4) up to reaching a first given temperature having a value below said first temperature target.

Abstract: A method for estimating the absolute size dimensions of a test object based on image data of the test object, namely a face or part of a person. The method includes receiving image data of the test object, determining a first model of the test object based on the received image data, and aligning and scaling the first model to a first average model that includes an average of a plurality of first models of reference objects being faces or parts of faces of reference persons. The first models of the reference objects are of a same type as the first model of the test object.

Abstract: The invention relates to a portable device (1100) comprising a bottom surface (BS) intended to be in contact with a textile (TXT). The portable device comprises an image sensor (5) for taking an image of a textile, and an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8a) for executing an algorithm stored in the portable device, using the taken image as an input of said algorithm, to obtain a classification of the textile. The image sensor and the control unit are integrated within the portable device. The image sensor has an active surface sensitive to light, which is oriented compared to said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees; and/or the illumination system (6) has a light source oriented compared to the said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees.

Abstract: A system and method are provided which use a machine learning algorithm to obtain a learned annotation of objects in one or more scales of a multiscale image. A viewing window (300) is provided for viewing the multiscale image. The viewing window is configurable on the basis of a magnification factor, which selects one of the plurality of scales for viewing, and a spatial offset parameter. A user may provide a manual annotation of an object in the viewing window, which is then used as training feedback in the learning of the machine learning algorithm. To enable the user to more effectively provide the manual annotation, the magnification factor and the spatial offset parameter for the viewing window may be automatically determined, namely by the system and method determining where in the multiscale image the manual annotation of the object would have sufficient influence on the learned annotation provided by the machine learning algorithm.

Abstract: Two or more images are taken wherein during the image taking a focal sweep is performed. The exposure intensity is modulated during the focal sweep and done so differently for the images. This modulation provides for a watermarking of depth information in the images. The difference in exposure during the sweep watermarks the depth information differently in the images. By comparing the images a depth map for the images can be calculated. A camera system has a lens and a sensor and a means for performing a focal sweep and means for modulating the exposure intensity during the focal sweep. Modulating the exposure intensity can be done by modulating a light source or the focal sweep or modulating the transparency of a transparent medium in the light path.

Abstract: An electronic apparatus includes a compilation unit structured to receive a plurality of different 3-D models of a patient's face, to compare the different 3-D models of the patient's face and to determine additional information about the patient's face based on the comparison, wherein the additional information includes at least one of a location of hard tissue, a depth of soft tissue, and a compliance of soft tissue, and wherein the patient's face is manipulated between the different 3-D models.

Abstract: A method of assisting in selection of a particular mask from among a plurality of masks, the method comprising: generating a plurality of augmented faces, each augmented face corresponding to a respective mask of the plurality of masks; and associating each augmented face with a respective mask of the plurality of masks.

Abstract: The present invention relates to a method for estimating absolute size dimensions of a test object (32) based on image data of the test object (32), the test object (32) being a face or part of a face of a test person, the method comprising the steps of: —receiving (S101) image data of the test object (32); —determining (S102) a first model (30) of the test object (32) based on the received image data, wherein the first model (30) has an unknown scale; —aligning and scaling the first model (30) of the test object (32) to a first average model, wherein the first average model includes an average of a plurality of first models of reference objects being faces or parts of faces of reference persons, wherein said first models of the reference objects are of a same type as the first model (30) of the test object (32) and have an unknown scale; —determining a shape difference between the test object (32) and an average of the reference objects by determining a difference between the aligned and scaled first model o

Abstract: A series of structured lighting patterns are projected on an object. Each successive structured lighting pattern has a first and second subset of intensity features such as edges between light and dark areas. The intensity features of the first set coincide spatially with intensity features from either the first or second subset from a preceding structured lighting pattern in the series. Image positions are detected where the intensity features of the first and second subset of the structured lighting patterns are visible in the images. Image positions where the intensity features of the first subset are visible are associated with the intensity features of the first subset, based on the associated intensity features of closest detected image positions with associated intensity features in the image obtained with a preceding structured lighting pattern in said series.

Abstract: The present invention relates to a scanning device (10, 10?) for scanning an object (12), wherein the scanning device (10) comprises a projection unit (16) for projecting an alignment image (28) onto the object (12), said alignment image (28) comprising a main pattern (26), an image capturing unit (18) for capturing a live camera image (30) of the object (12), said live camera image (30) comprising a derivative pattern (32) of the main pattern (26), the derivative pattern (32) representing said projected alignment image (28) as seen from the image capturing unit viewpoint, and an alignment unit (22, 22?) for providing an indication of a correct position and/or orientation of the scanning device (10) with respect to the scanned object (12) on the basis of the captured live camera image (30).

Abstract: Two or more images are taken wherein during the image taking a focal sweep is performed. The exposure intensity is modulated during the focal sweep and done so differently for the images. This modulation provides for a watermarking of depth information in the images. The difference in exposure during the sweep watermarks the depth information differently in the images. By comparing the images a depth map for the images can be calculated. A camera system has a lens and a sensor and a means for performing a focal sweep and means for modulating the exposure intensity during the focal sweep. Modulating the exposure intensity can be done by modulating a light source or the focal sweep or modulating the transparency of a transparent medium in the light path.