Show simple item record

dc.contributor.authorBharatharaj, Jen_NZ
dc.contributor.authorHuang, Len_NZ
dc.contributor.authorElara Mohan, Ren_NZ
dc.contributor.authorPathmakumar, Ten_NZ
dc.contributor.authorKrageloh, Cen_NZ
dc.contributor.authorAl-Jumaily, Aen_NZ
dc.date.accessioned2018-07-04T04:24:23Z
dc.date.available2018-07-04T04:24:23Z
dc.date.copyright2018-07-03en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/11644
dc.description.abstractExtensive research has been conducted in human head pose detection systems and several applications have been identified to deploy such systems. Deep learning based head pose detection is one such method which has been studied for several decades and reports high success rates during implementation. Across several pet robots designed and developed for various needs, there is a complete absence of wearable pet robots and head pose detection models in wearable pet robots. Designing a wearable pet robot capable of head pose detection can provide more opportunities for research and development of such systems. In this paper, we present a novel head pose detection system for a wearable parrot-inspired pet robot using images taken from the wearer’s shoulder. This is the first time head pose detection has been studied in wearable robots and using images from a side angle. In this study, we used AlexNet convolutional neural network architecture trained on the images from the database for the head pose detection system. The system was tested with 250 images and resulted in an accuracy of 94.4% across five head poses, namely left, left intermediate, straight, right, and right intermediate.
dc.relation.urihttp://www.mdpi.com/2076-3417/8/7/1081en_NZ
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
dc.titleHead Pose Detection for aWearable Parrot-Inspired Robot Based on Deep Learningen_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.3390/app8071081en_NZ
aut.relation.endpage1095
aut.relation.issue7en_NZ
aut.relation.pages14
aut.relation.startpage1081
aut.relation.volume8en_NZ
pubs.elements-id340564
aut.relation.journalApplied Sciencesen_NZ


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record