Data

Frontal depth images for an assessment of Gait Energy Volume (GEV)

Queensland University of Technology
Fookes, Clinton ; Chen, Daniel ; Sivapalan , Sabesan ; Denman, Simon ; Sridharan, Sridha
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/09/585c81530c107&rft.title=Frontal depth images for an assessment of Gait Energy Volume (GEV)&rft.identifier=10.4225/09/585c81530c107&rft.publisher=Queensland University of Technology&rft.description=This dataset was gathered to explore the application of frontally acquired depth images to an assessment of Gait Energy Volumes. The dataset consists of 15 subjects walking towards a camera at two different speeds, 'normal' and 'fast'. Five sequences were recorded for each subject and class, with each sequence covering an average of two to three gait cycles.The dataset is captured at approximately 30 fps using the Microsoft Kinect. Colour video was also recorded but was not used. &rft.creator=Fookes, Clinton &rft.creator=Chen, Daniel &rft.creator=Sivapalan , Sabesan &rft.creator=Denman, Simon &rft.creator=Sridharan, Sridha &rft.date=2016&rft.edition=1&rft.relation=http://goo.gl/BllI9g&rft.coverage=153.025013,-27.476409&rft_rights=© Queensland University of Technology, 2012.&rft_rights=Creative Commons Attribution-Share Alike 3.0 http://creativecommons.org/licenses/by-sa/3.0/au/&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft_subject=Image processing &rft_subject=Frontal depth images&rft_subject=Gait energy image &rft_subject=Gait energy volume &rft_subject=Computer vision &rft_subject=Artifical intelligence and image processing&rft.type=dataset&rft.language=English Access the data
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CC-BY-SA

Creative Commons Attribution-Share Alike 3.0
http://creativecommons.org/licenses/by-sa/3.0/au/

© Queensland University of Technology, 2012.

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In addition to citing our paper, we kindly request that the following text be included in an acknowledgements section at the end of your publications:

We would like to thank the SAIVT Research Labs at Queensland University of Technology (QUT) for freely supplying us with the SAIVT-DGD database for our research.

Contact Information

Postal Address:
Dr Sabesan Sivapalan
Ph: +61 7 3138 1414

sivapalen.sabesan@qut.edu.au

Full description

This dataset was gathered to explore the application of frontally acquired depth images to an assessment of Gait Energy Volumes.

The dataset consists of 15 subjects walking towards a camera at two different speeds, 'normal' and 'fast'. Five sequences were recorded for each subject and class, with each sequence covering an average of two to three gait cycles.

The dataset is captured at approximately 30 fps using the Microsoft Kinect. Colour video was also recorded but was not used.

Data time period: 2011 to 31 12 2011

This dataset is part of a larger collection

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153.02501,-27.47641

153.025013,-27.476409

Subjects
Artifical intelligence and image processing | Computer vision | Frontal depth images | Gait energy image | Gait energy volume | Information and Computing Sciences | Image processing |

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