Statistical segmentation and recognition of fingertip trajectories for a gesture interface

Authors:
Kazuhiro Morimoto;Chiyomi Miyajima;Norihide Kitaoka;Katunobu Itou;Kazuya Takeda
Affiliations:
Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Nagoya University, Nagoya, Japan;Hosei University, Tokyo, Japan;Nagoya University, Nagoya, Japan
Venue:
Proceedings of the 9th international conference on Multimodal interfaces
Year:
2007

Citing 4
Cited 0

Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review

IEEE Transactions on Pattern Analysis and Machine Intelligence
Hidden Markov Models for Speech Recognition

Hidden Markov Models for Speech Recognition
GestureWrist and GesturePad: Unobtrusive Wearable Interaction Devices

ISWC '01 Proceedings of the 5th IEEE International Symposium on Wearable Computers
Sketch based interfaces: early processing for sketch understanding

Proceedings of the 2001 workshop on Perceptive user interfaces

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a virtual push button interface created by drawing a shape or line in the air with a fingertip. As an example of such a gesture-based interface, we developed a four-button interface for entering multi-digit numbers by pushing gestures within an invisible 2x2 button matrix inside a square drawn by the user. Trajectories of fingertip movements entering randomly chosen multi-digit numbers are captured with a 3D position sensor mounted on the the forefinger's tip. We propose a statistical segmentation method for the trajectory of movements and a normalization method that is associated with the direction and size of gestures. The performance of the proposed method is evaluated in HMM-based gesture recognition. The recognition rate of 60.0% was improved to 91.3% after applying the normalization method.