2019-08-29T11:11:42 n15570

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

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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.

Access rights

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.

Geographical area of data collection



Sivapalan, Sabesan, Chen, Daniel, Denman, Simon, Sridharan, Sridha, & Fookes, Clinton B. (2011) Gait energy volumes and frontal gait recognition using depth images. In "Proceeding of the International Joint Conference on Biometrics", Washington DC, USA, available at http://eprints.qut.edu.au/46382/

Research areas

Artifical intelligence and image processing
Computer vision
Gait energy volume
Gait energy image
Frontal depth images
Image processing
Information and computing sciences

Cite this collection

Fookes, Clinton; Chen, Daniel; Sivapalan , Sabesan; Denman, Simon; Sridharan, Sridha (2016): Frontal depth images for an assessment of Gait Energy Volume (GEV). Queensland University of Technology. (Dataset) https://doi.org/10.4225/09/585c81530c107

Related information

TechTalks presentation http://goo.gl/BllI9g
Dataset also know as the SAIVT-DGD Database https://wiki.qut.edu.au/display/saivt/SAIVT-DGD+Database

Data file types



Creative Commons Attribution-Share Alike 4.0 (CC-BY-SA)


© Queensland University of Technology, 2012.

Dates of data collection

From 2011-01-01 to 2011-12-31


Was collected by
Clinton Fookes  (Researcher)
Daniel Chen   (Researcher)
Sabesan Sivapalan   (Researcher)
Simon Denman  (Researcher)
Sridha Sridharan  (Researcher)


Name: Dr Sabesan Sivapalan
Phone: +61 7 3138 1414


Date record created:
Date record modified:
Record status:
Published - Open Access