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An architecture for automatic gesture analysis

Authors:

E. Ardizzone,

A. Chella,

R. PirroneAuthors Info & Claims

AVI '00: Proceedings of the working conference on Advanced visual interfaces

Pages 205 - 210

https://doi.org/10.1145/345513.345317

Published: 01 May 2000 Publication History

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Abstract

The field of human-computer interaction has been widely investigated in the last years, resulting in a variety of systems used in different application fields like virtual reality simulation environments, software user interfaces, and digital library systems.

A very crucial part of all these systems is the input module which is devoted to recognize the human operator in terms of tracking and/or recognition of human face, arms position, hand gestures, and so on.

In this work a software architecture is presented, for the automatic recognition of human arms poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially structured environment can be trained by a human operator to follow particular routes in order to perform its task quickly. The system is able to recognize and classify some different poses of the operator's arms as direction commands like “turn-left”, “turn-right”, “go-straight”, and so on.

A binary image of the operator silhouette is obtained from the gray-level input. Next, a slice centered on the silhouette itself is processed in order to compute the eigenvalues vector of the pixels co-variance matrix. This kind of information is strictly related to the shape of the contour of the operator figure, and can be usefully employed in order to assess the arms' position. Finally, a support vector machine (SVM) is trained in order to classify different poses, using the eigenvalues array.

A detailed description of the system is presented along with some remarks on the statistical analysis we used, and on SVM. The experimental results, and an outline of the usability of the system as a generic shape classification tool are also reported.

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Cited By

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Cruz-Benito JTherón RGarcía-Peñalvo F(2016)Software Architectures Supporting Human-Computer Interaction Analysis: A Literature ReviewLearning and Collaboration Technologies10.1007/978-3-319-39483-1_12(125-136)Online publication date: 17-Jul-2016
https://dl.acm.org/doi/10.1007/978-3-319-39483-1_12
(2016)Ground Control SystemsRemotely Piloted Aircraft Systems: A Human Systems Integration Perspective10.1002/9781118965900.ch4(63-108)Online publication date: 12-Aug-2016
https://doi.org/10.1002/9781118965900.ch4

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Published In

AVI '00: Proceedings of the working conference on Advanced visual interfaces

May 2000

317 pages

ISBN:1581132522

DOI:10.1145/345513

Chairmen:
Stefano Levialdi
Univ. di Roma “La Sapienza”, Roma, Italy
,
Vita Di Gesù
Univ. di Patermo, Patermo, Italy
,
Laura Tarantino
Univ. degli Studi dell'Aquila, L'Aquila, Italy

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 2000

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SIGMM
SIGCHI
University of L'Aquila

AVI00: Advanced Visual Interfaces

Palermo, Italy

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Cruz-Benito JTherón RGarcía-Peñalvo F(2016)Software Architectures Supporting Human-Computer Interaction Analysis: A Literature ReviewLearning and Collaboration Technologies10.1007/978-3-319-39483-1_12(125-136)Online publication date: 17-Jul-2016
https://dl.acm.org/doi/10.1007/978-3-319-39483-1_12
(2016)Ground Control SystemsRemotely Piloted Aircraft Systems: A Human Systems Integration Perspective10.1002/9781118965900.ch4(63-108)Online publication date: 12-Aug-2016
https://doi.org/10.1002/9781118965900.ch4

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Automatic Gesture Recognition for Intelligent Human-Robot Interaction

Automatic Detection of Naturalistic Hand-over-Face Gesture Descriptors

Automatic Analysis of Naturalistic Hand-Over-Face Gestures