TST Intake Monitoring dataset v1
- Citation Author(s):
- Submitted by:
- Susanna Spinsante
- Last updated:
- DOI:
- 10.21227/H2G59T
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Abstract
The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.
Instructions:
– The dataset is composed by the executions of food and drink intake actions performed by 35 young actors.
Each actor repeated each action 1/2 times, generating a total number of 48 sequences. For each sequence, the following data are available:
- depth frames, resolution of 320x240, captured by Kinect v1 in top-view configuration;
- coordinates of nodes computed by three unsupervised algorithms (SOM, SOM_Ex, GNG) and coordinates of ground-truth nodes (only for hands and head, manually identified): http://www.tlc.dii.univpm.it/dbkinect/FoodIntake/LoadNets_And_GT.zip
This code can be used to read data with MATLAB, and to convert the depth frame from pixel domain to the point cloud domain:
http://www.tlc.dii.univpm.it/dbkinect/FoodIntake/FromDepth2PC.zip
If you use the dataset, please cite the following paper:
S. Gasparrini, E. Cippitelli, E. Gambi, S. Spinsante and F. Florez-Revuelta, “Performance Analysis of Self-Organising Neural Networks Tracking Algorithms for Intake Monitoring Using Kinect,” 1st IET International Conference on Technologies for Active and Assisted Living (TechAAL), 6th November 2015, Kingston upon Thames (UK).
