Chasing feet in the wild: A proposed egocentric motion-aware gait assessment tool

Mina Nouredanesh, Aaron Li, Alan Godfrey, Jesse Hoey, James Tung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)
11 Downloads (Pure)

Abstract

Despite advances in gait analysis tools, including optical motion capture and wireless electrophysiology, our understanding of human mobility is largely limited to controlled conditions in a clinic and/or laboratory. In order to examine human mobility under natural conditions, or the 'wild', this paper presents a novel markerless model to obtain gait patterns by localizing feet in the egocentric video data. Based on a belt-mounted camera feed, the proposed hybrid FootChaser model consists of: 1) the FootRegionProposer, a ConvNet that proposes regions with high probability of containing feet in RGB frames (global appearance of feet), and 2) LocomoNet, which is sensitive to the periodic gait patterns, and further examines the temporal content in the stacks of optical low corresponding to the proposed region. The LocomoNet signicantly boosted the overall model's result by ltering out the false positives proposed by the FootRegionProposer. This work advances our long-term objective to develop novel markerless models to extract spatiotemporal gait parameters, particularly step width, to complement existing inertial measurement unit (IMU) based methods.
Original languageEnglish
Title of host publicationComputer Vision – ECCV 2018
Subtitle of host publication15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings
EditorsVittorio Ferrari, Martial Hebert, Cristian Sminchisescu, Yair Weiss
PublisherSpringer
Pages176-192
Number of pages17
Volume1
ISBN (Electronic)9783030012465
ISBN (Print)9783030012458
DOIs
Publication statusE-pub ahead of print - 23 Jan 2019
EventEuropean Conference on Computer Vision 2018 - Munich, Germany
Duration: 8 Sep 201814 Sep 2018
https://eccv2018.org/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11134
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceEuropean Conference on Computer Vision 2018
CountryGermany
CityMunich
Period8/09/1814/09/18
Internet address

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