Abstract: The present invention provides methods and systems for determining mental states of a user based on mental load index, comprising: analysing image data to identify feature(s) of at least one eye while presenting user with dynamic physiological-responsive stimuli; calculating, based on the identified feature(s), spatiotemporal fluctuations over time for the feature(s); calculating, based on the spatiotemporal fluctuations, spectral pattern(s) having a first and second frequency; calculating mental load pattern(s) by bounding ratio between the spectral patterns for the first and second frequencies in time interval(s) corresponding to stimuli level changes; identifying correlation between each mental load pattern(s) and the stimuli level in the time interval(s); and determining, based on the correlation, a mental load index comprising time interval(s) corresponding to a plurality of mental states identified by comparing each mental load pattern(s) to a threshold; and classifying mental state(s) based on the ment

Abstract: A method for updating response profiles of drivers, comprising receiving a plurality of images captured by one or more imaging sensors deployed to monitor one or more eyes of a driver of a vehicle, analyzing at least some of the plurality of images to identify one or more eye dynamics signal patterns preceding one or more abnormal driving events occurring in an environment of the vehicle, updating a response profile of the driver based on an association of one or more of the abnormal driving event and the one or more of the identified eye dynamics signal patterns and providing information based on the updated response profile of the driver. The provided information is configured to enable one or more control systems of the vehicle to predict an imminent abnormal driving event based on an eye dynamics signal of the driver.

Abstract: A method for defining a robotic machine task. The method comprises a) collecting a sequence of a plurality of images showing at least one demonstrator performing at least one manipulation of at least one object, b) performing an analysis of said sequence of a plurality of images to identify demonstrator body parts manipulating said at least one object and said at least one manipulation of said at least one object, c) determining at least one robotic machine movement to perform said task, and d) generating at least one motion command for instructing said robotic machine to perform said task.

Abstract: The present invention provides methods and systems for determining mental states of a user based on mental load index, comprising: analysing image data to identify feature(s) of at least one eye while presenting user with dynamic physiological-responsive stimuli; calculating, based on the identified feature(s), spatiotemporal fluctuations over time for the feature(s); calculating, based on the spatiotemporal fluctuations, spectral pattern(s) having a first and second frequency; calculating mental load pattern(s) by bounding ratio between the spectral patterns for the first and second frequencies in time interval(s) corresponding to stimuli level changes; identifying correlation between each mental load pattern(s) and the stimuli level in the time interval(s); and determining, based on the correlation, a mental load index comprising time interval(s) corresponding to a plurality of mental states identified by comparing each mental load pattern(s) to a threshold; and classifying mental state(s) based on the ment

Abstract: A method of creating a real time synthetic model tracking a dynamic physical entity, comprising: a) Receiving multiple points extracted from a sequence of 3D information depicting a dynamic physical entity, each point is associated with position and photometric information. b) Identifying, within the multiply of points, a cloud point which includes multiple entity representative points which portray a surface of the dynamic physical entity. c) Generating a points-surface for a synthetic model by creating spatial presentation of the entity representative points through calculation of principal curvatures for each entity representative point according to the respective position information. d) Generating a continuous surface for the synthetic model by texturing ellipsoidal shapes created for each entity representative point according to the respective photometric information.

Abstract: A method of creating a real time synthetic model tracking a dynamic physical entity, comprising: a) Receiving multiple points extracted from a sequence of 3D information depicting a dynamic physical entity, each point is associated with position and photometric information. b) Identifying, within the multiply of points, a cloud point which includes multiple entity representative points which portray a surface of the dynamic physical entity. c) Generating a points-surface for a synthetic model by creating spatial presentation of the entity representative points through calculation of principal curvatures for each entity representative point according to the respective position information. d) Generating a continuous surface for the synthetic model by texturing ellipsoidal shapes created for each entity representative point according to the respective photometric information.

Abstract: A method for defining a robotic machine task. The method comprises a) collecting a sequence of a plurality of images showing at least one demonstrator performing at least one manipulation of at least one object, b) performing an analysis of said sequence of a plurality of images to identify demonstrator body parts manipulating said at least one object and said at least one manipulation of said at least one object, c) determining at least one robotic machine movement to perform said task, and d) generating at least one motion command for instructing said robotic machine to perform said task.

Abstract: A method for defining a robotic machine task. The method comprises a) collecting a sequence of a plurality of images showing at least one demonstrator performing at least one manipulation of at least one object, b) performing an analysis of said sequence of a plurality of images to identify demonstrator body parts manipulating said at least one object and said at least one manipulation of said at least one object, c) determining at least one robotic machine movement to perform said task, and d) generating at least one motion command for instructing said robotic machine to perform said task.

Abstract: A method of creating a real time synthetic model tracking a dynamic physical entity, comprising: a) Receiving multiple points extracted from a sequence of 3D information depicting a dynamic physical entity, each point is associated with position and photometric information. b) Identifying, within the multiply of points, a cloud point which includes multiple entity representative points which portray a surface of the dynamic physical entity. c) Generating a points-surface for a synthetic model by creating spatial presentation of the entity representative points through calculation of principal curvatures for each entity representative point according to the respective position information. d) Generating a continuous surface for the synthetic model by texturing ellipsoidal shapes created for each entity representative point according to the respective photometric information.

Abstract: A method for defining a robotic machine task. The method comprises a) collecting a sequence of a plurality of images showing at least one demonstrator performing at least one manipulation of at least one object, b) performing an analysis of said sequence of a plurality of images to identify demonstrator body parts manipulating said at least one object and said at least one manipulation of said at least one object, c) determining at least one robotic machine movement to perform said task, and d) generating at least one motion command for instructing said robotic machine to perform said task.