Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE
Abstract
The area of activity identification is maturing well in the HCI and ubiquitous computing fields. However, although algorithm development is proceedings well, without publicly available datasets on which to compare results it is difficult to consolidate the disparate work being done. This problem exists because realistic datasets describing human activity are difficult and expensive to gather and because there are significant barriers to releasing the data once gathered. We review positive recent development with the release of two high-quality datasets. From our experiences using these datasets we list some recommendations for the gathering and release of future datasets. Finally, we propose a strategy of our own for gathering a new dataset from these recommendations.
DOI
https://doi.org/10.21427/maa6-0479
Recommended Citation
Coyle, L., Ye, J. & Knox, S. (2009). Gathering Datasets for Activity Identification. CHI 2009, Boston, USA. 4-9 April. doi:10.21427/maa6-0479
Publication Details
Developing. Shared Home Behavior Datasets to Advance HCI and Ubiquitous Computing Research. Workshop at CHI 2009, Boston, USA