1. A method for analyzing or resolving ambiguities in image recognition for gesture, emotion, or expression recognition for a human, said method comprising: an input device receiving a first image of a body or facial part of said human from a source; an analyzer module segmenting a first part of said first image and a second part of said first image; retrieving said first part of said first image and said second part of said first image; a reference database storing gestures, emotions, or expressions; said reference database referring to a rules engine for definitions of said gestures, emotions, or expressions; said rules engine defining said gestures, emotions, or expressions, based on relationships between parts of an image, for said body or facial part of said human; a processor determining Z-valuation for one or more parameters for one or more relationships between said first part of said first image and said second part of said first image; wherein said Z-valuation relates to reliability or confidence of data; said processor determining a first gesture, emotion, or expression, for said human, based on said Z-valuation and said one or more parameters for said one or more relationships between said first part of said first image and said second part of said first image, by comparing to said reference database, using said rules engine.
1. A method for analyzing or resolving ambiguities in image recognition for gesture, emotion, or expression recognition for a human, said method comprising: an input device receiving a first image of a body or facial part of said human from a source; an analyzer module segmenting a first part of said first image and a second part of said first image; retrieving said first part of said first image and said second part of said first image; a reference database storing gestures, emotions, or expressions; said reference database referring to a rules engine for definitions of said gestures, emotions, or expressions; said rules engine defining said gestures, emotions, or expressions, based on relationships between parts of an image, for said body or facial part of said human; a processor determining Z-valuation for one or more parameters for one or more relationships between said first part of said first image and said second part of said first image; wherein said Z-valuation relates to reliability or confidence of data; said processor determining a first gesture, emotion, or expression, for said human, based on said Z-valuation and said one or more parameters for said one or more relationships between said first part of said first image and said second part of said first image, by comparing to said reference database, using said rules engine. 5. The method for analyzing or resolving ambiguities in image recognition for gesture, emotion, or expression recognition for a human, as recited in claim 1 , wherein said method is for classifying eye expression.