Living skin tissue tracking in video stream

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.

A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to:

• receive, as input, a video sequence comprising a plurality of frames and depicting a scene;
• detect, in each of said frames, one or more regions of interest (ROI) associated with an object in said scene;
• extract, 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, apply 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.