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

Amin Dadgar, Guido Brunnett

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 Harvard Style

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 - Volume 4: VISAPP, ISBN 978-989-758-290-5, pages 121-128. DOI: 10.5220/0006591601210128


in Bibtex Style

@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 - Volume 4: VISAPP,},
year={2018},
pages={121-128},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006591601210128},
isbn={978-989-758-290-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - 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
AU - Dadgar A.
AU - Brunnett G.
PY - 2018
SP - 121
EP - 128
DO - 10.5220/0006591601210128