Abstract: Embodiments of the present disclosure include receiving a sequence of images of a face of a user. A three-dimensional (3D) model of the face is generated and 3D facial points associated with flat facial surfaces are determined. The 3D facial points are projected onto a screen coordinate plane to produce a two-dimensional (2D) facial points. A hue is determined for each pixel associated with each of the 2D facial points in each image. A mean hue value is determined for each image. A spectral representation of a variation in each mean hue value across the sequence of images is determined. A frequency of a main hue is determined based on a largest weight of the variation in each mean hue value. A heart rate of the user is determined based on facial blood circulation according to the frequency of the main hue, and an activity recommendation is displayed.

Abstract: Embodiments of the present disclosure include receiving a sequence of images of a face of a user. A three-dimensional (3D) model of the face is generated and 3D facial points associated with flat facial surfaces are determined. The 3D facial points are projected onto a screen coordinate plane to produce a two-dimensional (2D) facial points. A hue is determined for each pixel associated with each of the 2D facial points in each image. A mean hue value is determined for each image. A spectral representation of a variation in each mean hue value across the sequence of images is determined. A frequency of a main hue is determined based on a largest weight of the variation in each mean hue value. A heart rate of the user is determined based on facial blood circulation according to the frequency of the main hue, and an activity recommendation is displayed.

Abstract: In some embodiments, the present invention provides for an exemplary system that may include at least the following components: a camera component, where the camera component is configured to acquire a visual input, where the visual input includes a face of a person; a processor configured to: obtain the visual input; apply a face detection algorithm to detect a presence of the face within the visual input; extract a vector of at least one feature of the face; match the vector to a stored profile of the person to identify the person; fit, based on person-specific meta-parameters, a three-dimensional morphable face model (3DMFM) to obtain a person-specific 3DMFM of the one person; apply a facial expression detection algorithm to the person-specific 3DMFM to determine a person-specific facial expression; and cause to perform at least one activity associated with the person based at least in part on the person-specific facial expression of the person.

Abstract: In some embodiments, the present invention provides for an exemplary system that may include at least the following components: a camera component, where the camera component is configured to acquire a visual input, where the visual input includes a face of a person; a processor configured to: obtain the visual input; apply a face detection algorithm to detect a presence of the face within the visual input; extract a vector of at least one feature of the face; match the vector to a stored profile of the person to identify the person; fit, based on person-specific meta-parameters, a three-dimensional morphable face model (3DMFM) to obtain a person-specific 3DMFM of the ne person; apply a facial expression detection algorithm to the person-specific 3DMFM to determine a person-specific facial expression; and cause to perform at least one activity associated with the person based at least in part on the person-specific facial expression of the person.

Abstract: In some embodiments, the present invention provides for an exemplary system that may include at least the following components: a camera component, where the camera component is configured to acquire a visual input, where the visual input includes a face of a person; a processor configured to: obtain the visual input; apply a face detection algorithm to detect a presence of the face within the visual input; extract a vector of at least one feature of the face; match the vector to a stored profile of the person to identify the person; fit, based on person-specific meta-parameters, a three-dimensional morphable face model (3DMFM) to obtain a person-specific 3DMFM of the ne person; apply a facial expression detection algorithm to the person-specific 3DMFM to determine a person-specific facial expression; and cause to perform at least one activity associated with the person based at least in part on the person-specific facial expression of the person.