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Multi-Forest Classification and Layered Exhaustive Search using a Fully Hierarchical Hand Posture/Gesture Database

Topics: Device Calibration, Characterization and Modeling; Event and Human Activity Recognition; Human and Computer Interaction; Image-Based Modeling and 3D Reconstruction; Machine Learning Technologies for Vision; Shape Representation and Matching

Authors: Amin Dadgar and Guido Brunnett

Affiliation: Chemnitz University of Technology, Germany

Keyword(s): Fully-Hierarchical Hand Posture Database, Multi-Forest Classification, Layered-Exhaustive Search.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Device Calibration, Characterization and Modeling ; Enterprise Information Systems ; Geometry and Modeling ; Human and Computer Interaction ; Human-Computer Interaction ; Image and Video Analysis ; Image Formation and Preprocessing ; Image-Based Modeling ; Pattern Recognition ; Shape Representation and Matching ; Software Engineering

Abstract: In this paper, we propose a systematic approach to building an entirely hierarchical hand posture database. The hierarchy provides the possibility of considering a large number of hand poses while requires a low time-space complexity for construction. Furthermore, two algorithms (random decision forest and exhaustive search) are chosen and tested on this database. We show that by utilizing such a database one will achieve better performances on classifiers’ training and search strategies (two main categories of the algorithms in the field of machine learning) compared with conventional (all-in-one-layer) databases.

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Paper citation in several formats:
Dadgar, A. and Brunnett, G. (2018). Multi-Forest Classification and Layered Exhaustive Search using a Fully Hierarchical Hand Posture/Gesture Database. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP; ISBN 978-989-758-290-5; ISSN 2184-4321, SciTePress, pages 121-128. DOI: 10.5220/0006591601210128

@conference{visapp18,
author={Amin Dadgar. and Guido Brunnett.},
title={Multi-Forest Classification and Layered Exhaustive Search using a Fully Hierarchical Hand Posture/Gesture Database},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP},
year={2018},
pages={121-128},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006591601210128},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP
TI - Multi-Forest Classification and Layered Exhaustive Search using a Fully Hierarchical Hand Posture/Gesture Database
SN - 978-989-758-290-5
IS - 2184-4321
AU - Dadgar, A.
AU - Brunnett, G.
PY - 2018
SP - 121
EP - 128
DO - 10.5220/0006591601210128
PB - SciTePress