Abstract: A method comprising receiving, as input, physiological parameters data measured in a human subject in response to an administered test question protocol comprising (a) a plurality of test question segments, each comprising at least one test question, and (b) a recovery period following each of the test question segments; determining a stress signal associated with the test question protocol, based, at least in part, on one or more states of stress detected in the physiological parameters data; temporally associating values of the stress signal with the plurality of test question segments and the recovery periods; and calculating, for at least some of the test question segments, a segment psychophysiological response score associated with the responses by the subject, based on an analysis of the temporally associated values of the stress signal.

Abstract: A method comprising: receiving, as input, a video sequence comprising a plurality of frames and depicting a scene; detecting, in each of said frames, one or more regions of interest (ROI) associated with an object in said scene; extracting, from each of said ROIs with respect to all of said frames, a feature set representing spectral reflectance; at a training stage, train a machine learning classifier on a training set comprising: (i) all of said feature sets, and (ii) labels indicating whether each of said ROIs depicts living skin tissue; and at an inference stage, applying said trained machine learning classifier to a target feature set extracted from a target ROI detected in a target video sequence, to determine whether said ROI depicts living skin tissue.

Abstract: A method comprising: receiving, as input, a video sequence comprising a plurality of frames and depicting a scene; detecting, in each of said frames, one or more regions of interest (ROI) associated with an object in said scene; extracting, from each of said ROIs with respect to all of said frames, a feature set representing spectral reflectance; at a training stage, train a machine learning classifier on a training set comprising: (i) all of said feature sets, and (ii) labels indicating whether each of said ROIs depicts living skin tissue; and at an inference stage, applying said trained machine learning classifier to a target feature set extracted from a target ROI detected in a target video sequence, to determine whether said ROI depicts living skin tissue.