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Hand gesture sequence recognition using inertial motion units (IMUs)

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cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid0000-0001-6747-9050
cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.departmentIndian Institute of Technology, Madras
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid14d63cfe-8b70-428a-aff3-36fb2848f587
cris.virtualsource.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.department14d63cfe-8b70-428a-aff3-36fb2848f587
dc.contributor.authorKavarthapu, Dilip Chakravarthy
dc.contributor.authorMitra, Kaushik
dc.date.accessioned2023-09-19T15:01:53Z
dc.date.available2023-09-19T15:01:53Z
dc.date.issued13-12-2018
dc.description.abstractUnlike approaches that classify single gesture at a time, we propose a deep learning based technique that can classify multiple gestures in one shot. This is specially suitable for applications that involves seamless gesture sequences such as sign language recognition, touch-less car assistance systems and gaming systems. We propose a Long Short Term Memory(LSTM) based deep network on the lines of an Encoder-Decoder architecture that classifies gesture sequence accurately in one go. We also show an empirical training strategy for our architecture which can achieve good results even with limited amount of collected data. Results from the experiments performed on labelled datasets from Inertial Motion Units (IMU) proves the efficiency and usefulness of the proposed method.
dc.identifier.doi10.1109/ACPR.2017.159
dc.identifier.scopus2-s2.0-85060512641
dc.identifier.urihttps://apicris.irins.org/handle/IITM2023/33853
dc.relation.ispartofseriesProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
dc.sourceProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
dc.subjectDeep learning
dc.subjectEncoder decoder network
dc.subjectGesture recognition
dc.subjectIMU
dc.subjectLSTM
dc.titleHand gesture sequence recognition using inertial motion units (IMUs)
dc.typeConference Proceeding
dspace.entity.typePublication
oaire.citation.endPage957
oaire.citation.startPage953
oairecerif.author.affiliation#PLACEHOLDER_PARENT_METADATA_VALUE#
oairecerif.author.affiliationIndian Institute of Technology, Madras
person.affiliation.cityChennai
person.affiliation.id60025757
person.affiliation.nameIndian Institute of Technology Madras
person.identifier.scopus-author-id57205560849
person.identifier.scopus-author-id26531669600
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