Detecting and tracking touch on an illuminated surface using a machine learning classifier

摘要

A method for touch detection that is performed by a touch processor in an optical touch detection system is provided. The method includes receiving an image of an illuminated surface in the optical touch detection system, wherein the image is captured by a camera in the optical touch detection system, identifying a set of candidate touch locations in the image, classifying the candidate touch locations in the set of candidate touch locations to generate a set of validated candidate touch locations, wherein classifying the candidate touch locations includes using a machine learning classifier to classify each candidate touch location as valid or invalid, wherein the machine learning classifier is trained to classify a candidate touch location based on a combination of features of the candidate touch location, and outputting a set of final touch locations.

主权项

1. A method for touch detection performed by a touch processor in an optical touch detection system, the method comprising:
receiving an image of an illuminated surface comprised in the optical touch detection system, wherein the image is captured by a camera comprised in the optical touch detection system; identifying a set of candidate touch locations in the image, wherein identifying a set of candidate touch locations comprises subtracting a background model from the image to generate a mean-subtracted image, filtering the mean-subtracted image with a filter having zero mean with coefficients of a same sign in a center of the filter surrounded by coefficients of an opposite sign such that a size of a central region corresponds to an expected size of a finger touch, and identifying local extrema in the filtered mean-subtracted image; classifying the candidate touch locations in the set of candidate touch locations to generate a set of validated candidate touch locations, wherein classifying the candidate touch locations comprises using a machine learning classifier to classify each candidate touch location as valid or invalid, wherein the machine learning classifier is trained to classify a candidate touch location based on a combination of features of the candidate touch location; and outputting a set of final touch locations.