Abstract: A body language system for determining a body language message of a living being in a context comprising an artificial intelligence system, said AI system running a computer program that: retrieves an image of said living being showing body language; labels said living being in said image, resulting in a labeled living being; determines said context from said image using a trained machine learning model; determines a baseline body language of said labeled living being from said image using a trained machine learning model; adapts a trained machine learning model of said AI system using said baseline body language and said context; applies the adapted trained machine learning model of said AI system to the one image for categorizing said body language resulting in a category, and applying said category for determining said body language message.

Abstract: A body language system for determining a body language message of a living being in a context comprising an artificial intelligence system, said AI system running a computer program that: retrieves an image of said living being showing body language; labels said living being in said image, resulting in a labeled living being; determines said context from said image using a trained machine learning model; determines a baseline body language of said labeled living being from said image using a trained machine learning model; adapts a trained machine learning model of said AI system using said baseline body language and said context; applies the adapted trained machine learning model of said AI system to the one image for categorizing said body language resulting in a category, and applying said category for determining said body language message.

Abstract: A body language system for determining a body language message of a living being in a context comprising an artificial intelligence system, said AI system running a computer program that: retrieves an image of said living being showing body language; labels said living being in said image, resulting in a labeled living being; determines said context from said image using a trained machine learning model; determines a baseline body language of said labeled living being from said image using a trained machine learning model; adapts a trained machine learning model of said AI system using said baseline body language and said context; applies the adapted trained machine learning model of said AI system to the one image for categorizing said body language resulting in a category, and applying said category for determining said body language message.

Abstract: A body language system for determining a body language message of a living being in a context comprising an artificial intelligence system, said AI system running a computer program that: retrieves an image of said living being showing body language; labels said living being in said image, resulting in a labeled living being; determines said context from said image using a trained machine learning model; determines a baseline body language of said labeled living being from said image using a trained machine learning model; adapts a trained machine learning model of said AI system using said baseline body language and said context; applies the adapted trained machine learning model of said AI system to the one image for categorizing said body language resulting in a category, and applying said category for determining said body language message.

Abstract: Some embodiments are directed to a system and a method for estimating gaze from a set of eye measurement points that are indicative of a gaze pattern of a user viewing a scene. Some other embodiments are directed to obtaining sets of eye measurement points from different users viewing the same scene. In another embodiment, the different sets of eye measurement points are mapped to a common coordinate system for reciprocal calibration In yet another embodiment, a scene transformation for mapping the common coordinate system to a coordinate system associated with the scene can be calculated by matching eye measurement points from the common coordinate system to interest points of the scene. The scene transformation is thereby calculated more accurately than individually calculated scene transformations, thereby providing a more accurate estimate of the gaze points.

Abstract: Some embodiments are directed to a system and a method for estimating gaze from a set of eye measurement points that are indicative of a gaze pattern of a user viewing a scene. Some other embodiments are directed to obtaining sets of eye measurement points from different users viewing the same scene. In another embodiment, the different sets of eye measurement points are mapped to a common coordinate system for reciprocal calibration. In yet another embodiment, a scene transformation for mapping the common coordinate system to a coordinate system associated with the scene can be calculated by matching eye measurement points from the common coordinate system to interest points of the scene. The scene transformation is thereby calculated more accurately than individually calculated scene transformations, thereby providing a more accurate estimate of the gaze points.