Open AccessVision‐Based Finger Action Recognition by Angle Detection and Contour Analysis
Author(s) -
Lee Daeho,
Lee SeungGwan
Publication year - 2011
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.11.0110.0313
Subject(s) - artificial intelligence , computer vision , computer science , position (finance) , tracking (education) , invariant (physics) , interface (matter) , mathematics , psychology , pedagogy , finance , bubble , maximum bubble pressure method , parallel computing , economics , mathematical physics
In this paper, we present a novel vision‐based method of recognizing finger actions for use in electronic appliance interfaces. Human skin is first detected by color and consecutive motion information. Then, fingertips are detected by a novel scale‐invariant angle detection based on a variable k ‐cosine. Fingertip tracking is implemented by detected region‐based tracking. By analyzing the contour of the tracked fingertip, fingertip parameters, such as position, thickness, and direction, are calculated. Finger actions, such as moving, clicking, and pointing, are recognized by analyzing these fingertip parameters. Experimental results show that the proposed angle detection can correctly detect fingertips, and that the recognized actions can be used for the interface with electronic appliances.