Head gestures recognition

Author

Ng, Pei Chi ; De Silva, Liyanage C.

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore

Volume

3

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

266

Abstract

We describe a system that automatically detects and recognizes human head gestures such as nodding and shaking in complex background conditions using a cheap Web camera under uncontrolled conditions. The images of the head, captured at 20 frames per second, are very noisy and are of a low resolution. The invariant moments of each image captured is extracted and is fed into a recognition system that uses discrete hidden Markov models (HMMs) to classify the head gestures. The system achieves an average success rate of 87%. The system can successfully run on any low to high end PC connected to a USB Web camera without any manual initialization

Keywords

gesture recognition; hidden Markov models; image classification; image resolution; image sequences; object detection; HMM; USB Web cam; Web camera; discrete hidden Markov models; gesture classification; head gesture detection; human head gesture recognition; nodding; shaking; Application software; Education; Facial features; Head; Hidden Markov models; Humans; Image resolution; Positron emission tomography; Robots; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2001. Proceedings. 2001 International Conference on

Conference_Location

Thessaloniki

Print_ISBN

0-7803-6725-1

Type

conf

DOI

10.1109/ICIP.2001.958102

Filename

958102