Vision‐Based Finger Action Recognition by Angle Detection and Contour Analysis

• Published in: ETRI journal Vol. 33; no. 3; pp. 415 - 422
• Main Authors: Lee, Daeho, Lee, SeungGwan
• Format: Journal Article
• Language: English
• Published: 한국전자통신연구원 01.06.2011
• Subjects: Fingertip detection; fingertip tracking; human‐machine interaction; machine vision; scale‐invariant angle detection; 전자/정보통신공학
• ISSN: 1225-6463; 2233-7326
• DOI: 10.4218/etrij.11.0110.0313

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.