Recognition of Deictic Gestures for Wearable Computing

Thomas B. Moeslund, Lau Nørgaard

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

3 Citations (Scopus)
355 Downloads (Pure)

Abstract

In modern society there is an increasing demand to access, record and manipulate large amounts of information. This has inspired a new approach to thinking about and designing personal computers, where the ultimate goal is to produce a truly wearable computer. In this work we present a non-invasive handgesture recognition system aimed at deictic gestures. Our system is based on the powerful Sequential Monte Carlo framework which is enhanced with respect to increased robustness. This is achieved by using ratios in the likelihood function together with two image cues: edges and skin color. The system proves to be fast, robust towards noise, and quick to lock on to the object (hand). All of which is achieved without the use of special lighting or special markers on the hands, hence our system is a non-invasive solution.

Original languageEnglish
Title of host publicationGesture in Human-Computer Interaction and Simulation
EditorsS. Gibet, N. Courty, J. F. Kamp
PublisherIEEE Computer Society Press
Publication date2006
Pages112-123
ISBN (Print)3540326243
Publication statusPublished - 2006
EventRecognition of Deictic Gestures for Wearable Computing -
Duration: 19 May 2010 → …

Conference

ConferenceRecognition of Deictic Gestures for Wearable Computing
Period19/05/2010 → …
SeriesLecture Notes In Artificial Intelligence
Number3881
ISSN0302-9743

Fingerprint

Wearable computers
Personal computers
Skin
Lighting
Color

Cite this

Moeslund, T. B., & Nørgaard, L. (2006). Recognition of Deictic Gestures for Wearable Computing. In S. Gibet, N. Courty, & J. F. Kamp (Eds.), Gesture in Human-Computer Interaction and Simulation (pp. 112-123). IEEE Computer Society Press. Lecture Notes In Artificial Intelligence, No. 3881
Moeslund, Thomas B. ; Nørgaard, Lau. / Recognition of Deictic Gestures for Wearable Computing. Gesture in Human-Computer Interaction and Simulation. editor / S. Gibet ; N. Courty ; J. F. Kamp. IEEE Computer Society Press, 2006. pp. 112-123 (Lecture Notes In Artificial Intelligence; No. 3881).
@inproceedings{667652b01fbe11dca5a4000ea68e967b,
title = "Recognition of Deictic Gestures for Wearable Computing",
abstract = "In modern society there is an increasing demand to access, record and manipulate large amounts of information. This has inspired a new approach to thinking about and designing personal computers, where the ultimate goal is to produce a truly wearable computer. In this work we present a non-invasive handgesture recognition system aimed at deictic gestures. Our system is based on the powerful Sequential Monte Carlo framework which is enhanced with respect to increased robustness. This is achieved by using ratios in the likelihood function together with two image cues: edges and skin color. The system proves to be fast, robust towards noise, and quick to lock on to the object (hand). All of which is achieved without the use of special lighting or special markers on the hands, hence our system is a non-invasive solution.",
author = "Moeslund, {Thomas B.} and Lau N{\o}rgaard",
year = "2006",
language = "English",
isbn = "3540326243",
series = "Lecture Notes In Artificial Intelligence",
publisher = "IEEE Computer Society Press",
number = "3881",
pages = "112--123",
editor = "S. Gibet and N. Courty and Kamp, {J. F.}",
booktitle = "Gesture in Human-Computer Interaction and Simulation",
address = "United States",

}

Moeslund, TB & Nørgaard, L 2006, Recognition of Deictic Gestures for Wearable Computing. in S Gibet, N Courty & JF Kamp (eds), Gesture in Human-Computer Interaction and Simulation. IEEE Computer Society Press, Lecture Notes In Artificial Intelligence, no. 3881, pp. 112-123, Recognition of Deictic Gestures for Wearable Computing, 19/05/2010.

Recognition of Deictic Gestures for Wearable Computing. / Moeslund, Thomas B.; Nørgaard, Lau.

Gesture in Human-Computer Interaction and Simulation. ed. / S. Gibet; N. Courty; J. F. Kamp. IEEE Computer Society Press, 2006. p. 112-123 (Lecture Notes In Artificial Intelligence; No. 3881).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - Recognition of Deictic Gestures for Wearable Computing

AU - Moeslund, Thomas B.

AU - Nørgaard, Lau

PY - 2006

Y1 - 2006

N2 - In modern society there is an increasing demand to access, record and manipulate large amounts of information. This has inspired a new approach to thinking about and designing personal computers, where the ultimate goal is to produce a truly wearable computer. In this work we present a non-invasive handgesture recognition system aimed at deictic gestures. Our system is based on the powerful Sequential Monte Carlo framework which is enhanced with respect to increased robustness. This is achieved by using ratios in the likelihood function together with two image cues: edges and skin color. The system proves to be fast, robust towards noise, and quick to lock on to the object (hand). All of which is achieved without the use of special lighting or special markers on the hands, hence our system is a non-invasive solution.

AB - In modern society there is an increasing demand to access, record and manipulate large amounts of information. This has inspired a new approach to thinking about and designing personal computers, where the ultimate goal is to produce a truly wearable computer. In this work we present a non-invasive handgesture recognition system aimed at deictic gestures. Our system is based on the powerful Sequential Monte Carlo framework which is enhanced with respect to increased robustness. This is achieved by using ratios in the likelihood function together with two image cues: edges and skin color. The system proves to be fast, robust towards noise, and quick to lock on to the object (hand). All of which is achieved without the use of special lighting or special markers on the hands, hence our system is a non-invasive solution.

M3 - Article in proceeding

SN - 3540326243

T3 - Lecture Notes In Artificial Intelligence

SP - 112

EP - 123

BT - Gesture in Human-Computer Interaction and Simulation

A2 - Gibet, S.

A2 - Courty, N.

A2 - Kamp, J. F.

PB - IEEE Computer Society Press

ER -

Moeslund TB, Nørgaard L. Recognition of Deictic Gestures for Wearable Computing. In Gibet S, Courty N, Kamp JF, editors, Gesture in Human-Computer Interaction and Simulation. IEEE Computer Society Press. 2006. p. 112-123. (Lecture Notes In Artificial Intelligence; No. 3881).