loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Authors: Naoki Nishida 1 ; Yasutomo Kawanishi 1 ; Daisuke Deguchi 2 ; Ichiro Ide 1 ; Hiroshi Murase 1 and Jun Piao 3

Affiliations: 1 Graduate School of Informatics, Nagoya University, Aichi, Japan ; 2 Information Strategy Office, Nagoya University, Aichi, Japan ; 3 Data Science Research Laboratories, NEC Corporation, Kanagawa, Japan

Keyword(s): Skeleton Orientation Alignment, Skeleton Representation Sequence, White Cane User Recognition.

Abstract: Recently, various facilities have been deployed to support visually impaired people. However, accidents caused by visual disabilities still occur. In this paper, to support the visually impaired people in public areas, we aim to identify the presence of a white cane user from a surveillance camera by analyzing the temporal transition of a human skeleton in a pedestrian image sequence represented as 2D coordinates. Our previously proposed method aligns the orientation of the skeletons to various orientations and identifies a white cane user from the corresponding sequences, relying on multiple classifiers related to each orientation. The method employs an exemplar-based approach to perform the alignment, and heavily depends on the number of exemplars and consumes excessive memory. In this paper, we propose a method to align 2D skeleton representation sequences to various orientations using the proposed Skeleton Orientation Alignment Networks (SOANets) based on an encoder-decoder model . Using SOANets, we can obtain 2D skeleton representation sequences aligned to various orientations, extract richer skeleton features, and recognize white cane users accurately. Results of an evaluation experiment shows that the proposed method improves the recognition rate by 16%, compared to the previous exemplar-based method. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.144.55.253

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Nishida, N.; Kawanishi, Y.; Deguchi, D.; Ide, I.; Murase, H. and Piao, J. (2020). SOANets: Encoder-decoder based Skeleton Orientation Alignment Network for White Cane User Recognition from 2D Human Skeleton Sequence. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-402-2; ISSN 2184-4321, pages 435-443. DOI: 10.5220/0008988204350443

@conference{visapp20,
author={Naoki Nishida. and Yasutomo Kawanishi. and Daisuke Deguchi. and Ichiro Ide. and Hiroshi Murase. and Jun Piao.},
title={SOANets: Encoder-decoder based Skeleton Orientation Alignment Network for White Cane User Recognition from 2D Human Skeleton Sequence},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2020},
pages={435-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008988204350443},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - SOANets: Encoder-decoder based Skeleton Orientation Alignment Network for White Cane User Recognition from 2D Human Skeleton Sequence
SN - 978-989-758-402-2
IS - 2184-4321
AU - Nishida, N.
AU - Kawanishi, Y.
AU - Deguchi, D.
AU - Ide, I.
AU - Murase, H.
AU - Piao, J.
PY - 2020
SP - 435
EP - 443
DO - 10.5220/0008988204350443

0123movie.net