Inertial-sensor-based walking action recognition using robust step detection and inter-class relationships

Ngo Thanh Trung, Yasushi Makihara, Hajime Nagahara, Yasuhiro Mukaigawa, Yasushi Yagi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This paper tackles a challenging problem of inertial sensor-based recognition for similar walking action classes. We solve two remaining problems of existing methods in the case of walking actions: action signal segmentation and recognition of similar action classes. First, to robustly segment the walking action under drastic changes such as speed, intensity, or style, we rely on the likelihood of heel strike that is computed employing a scale-space technique. Second, to improve the classification performance with similar action classes, we incorporate the inter-class relationship. In experiments, the proposed algorithms were positively validated with 97 subjects and five similar walking action classes, namely walking on flat ground, up/down stairs, and up/down a slope.

Original languageEnglish
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages3811-3814
Number of pages4
Publication statusPublished - 2012
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: Nov 11 2012Nov 15 2012

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other21st International Conference on Pattern Recognition, ICPR 2012
CountryJapan
CityTsukuba
Period11/11/1211/15/12

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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