Abstract: An eye segmentation system for determining a center point of an eye, a radius of an iris of the eye, and an area of interest from a white area (sclera) of the eye. The system includes at least one input interface that receives a facial image of a user, wherein the facial image is captured using an image capturing device and a data processing arrangement that receives the facial image of the user as input data and processes the facial image to segment an eye region of the facial image. The system determines an eye that is suitable for segmentation from a left eye and a right eye using at least one quality metric, determines a center point of the eye using at least one directional filter, determines, using the at least one directional filter, a radius of an iris of the eye from the center point of the eye.

Abstract: A method for augmenting point of interest in AR video. The method includes: extracting first frame of AR video depicting object being tracked including point of interest, by first pipeline; locating, in first frame set of feature points forming boundary of object; transferring frame with determined set of feature points to second pipeline; and by second pipeline determining coordinate system of set of feature points; calculating first location parameters of feature points; selecting first and second reference points from feature points, wherein first location parameters of point of interest are defined by first location parameters of first and second reference points; transmitting first location parameters of point of interest from second pipeline to first pipeline; and augmenting in first pipeline AR video with first location parameters of point of interest received from second pipeline.

Abstract: A method for hair analysis of a user. The method segmenting a hair region in an image of the user to obtain a segmented hair region image; identifying one or more dominant hair colour types in; determining RGB values of pixels of the one or more dominant hair colour types; implementing a hair colour dictionary with multiple tints of plurality of hair colours classified as different hair colour names, with each of the classified different hair colour names having a relative RGB value; comparing the determined RGB values of the pixels of the one or more dominant hair colour types and the relative RGB values for the classified different hair colour types to identify the relative RGB value with a minimum distance; and determining the hair colour name corresponding to the identified relative RGB value with the minimum distance.

Abstract: A method and a system for measuring a feature of persons. The method includes defining the feature of persons being measured. The method further includes measuring values of data points from a sample of digital images comprising the persons, according to the defined feature by a first algorithm. The method further includes generating a distribution curve of the measured values. The method further includes standardizing the measured values by implementing a hyperbolic tangent function transformation.

Abstract: A method for hair analysis of a user. The method segmenting a hair region in an image of the user to obtain a segmented hair region image; identifying one or more dominant hair colour types in; determining RGB values of pixels of the one or more dominant hair colour types; implementing a hair colour dictionary with multiple tints of plurality of hair colours classified as different hair colour names, with each of the classified different hair colour names having a relative RGB value; comparing the determined RGB values of the pixels of the one or more dominant hair colour types and the relative RGB values for the classified different hair colour types to identify the relative RGB value with a minimum distance; and determining the hair colour name corresponding to the identified relative RGB value with the minimum distance.

Abstract: A method and a system for measuring a feature of persons. The method includes defining the feature of persons being measured. The method further includes measuring values of data points from a sample of digital images comprising the persons, according to the defined feature by a first algorithm. The method further includes generating a distribution curve of the measured values. The method further includes standardizing the measured values by implementing a hyperbolic tangent function transformation.

Abstract: A method for augmenting point of interest in AR video. The method includes: extracting first frame of AR video depicting object being tracked including point of interest, by first pipeline; locating, in first frame set of feature points forming boundary of object; transferring frame with determined set of feature points to second pipeline; and by second pipeline determining coordinate system of set of feature points; calculating first location parameters of feature points; selecting first and second reference points from feature points, wherein first location parameters of point of interest are defined by first location parameters of first and second reference points; transmitting first location parameters of point of interest from second pipeline to first pipeline; and augmenting in first pipeline AR video with first location parameters of point of interest received from second pipeline.

Abstract: An eye segmentation system for determining a center point of an eye, a radius of an iris of the eye, and an area of interest from a white area (sclera) of the eye. The system includes at least one input interface that receives a facial image of a user, wherein the facial image is captured using an image capturing device and a data processing arrangement that receives the facial image of the user as input data and processes the facial image to segment an eye region of the facial image. The system determines an eye that is suitable for segmentation from a left eye and a right eye using at least one quality metric, determines a center point of the eye using at least one directional filter, determines, using the at least one directional filter, a radius of an iris of the eye from the center point of the eye.

Abstract: A method of determining facial areas from an image of a face of a user. The method includes obtaining, using a processing device, a set of image analysis modules. Further, the method includes receiving, using a communication device, the image of the face of the user. Yet further, the method includes receiving, using a communication device, an indication of a facial area of interest from the user. Moreover, the method includes selecting, using a processing device, from the set of image analysis modules an image analysis module associated with the indicated facial area of interest. Further, the method includes analyzing, using a processing device, the image of the face of the user to locate the indicated facial area of interest using the selected image analysis module. Yet further, the method includes rendering, using a processing device, in a user interface the image of the face of the user with an indication of the found facial area.

Abstract: Disclosed is a method of recommending at least one skin care product to a user. The method may include retrieving, using a communication device, a plurality of User Generated Content (UGC) corresponding to a plurality of users from at least one data source. Further, the method may include analysing, using a processing device, the plurality of UGC. Further, the method may include determining, using the processing device, each of at least one skin care product and at least one feedback associated with the skin care product based on the analysing. Further, the method may include storing, using a storage device, the at least one feedback and an association between the at least one feedback and an indication of at least one skin care product.

Abstract: A method of determining facial areas from an image of a face of a user. The method includes obtaining, using a processing device, a set of image analysis modules. Further, the method includes receiving, using a communication device, the image of the face of the user. Yet further, the method includes receiving, using a communication device, an indication of a facial area of interest from the user. Moreover, the method includes selecting, using a processing device, from the set of image analysis modules an image analysis module associated with the indicated facial area of interest. Further, the method includes analyzing, using a processing device, the image of the face of the user to locate the indicated facial area of interest using the selected image analysis module. Yet further, the method includes rendering, using a processing device, in a user interface the image of the face of the user with an indication of the found facial area.