TY  - CONF
ID  - Sagha2011_SMC
T1  - Benchmarking classification techniques using the Opportunity human activity dataset
A1  - Sagha, Hesam
A1  - Digumarti, Sundara Tejaswi
A1  - del R. Millán, José
A1  - Chavarriaga, Ricardo
A1  - Calatroni, Alberto
A1  - Roggen, Daniel
A1  - Tröster, Gerhard
TI  - Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Y1  - 2011
SP  - 36
EP  - 40
SN  - 1062-922X
M2  - doi: 10.1109/ICSMC.2011.6083628
KW  - OPPORTUNITY
N2  - Human activity recognition is a thriving research field. There are lots of studies in different sub-areas of activity recognition proposing different methods. However, unlike other applications, there is lack of established benchmarking problems for activity recognition. Typically, each research group tests and reports the performance of their algorithms on their own datasets using experimental setups specially conceived for that specific purpose. In this work, we introduce a versatile human activity dataset conceived to fill that void. We illustrate its use by presenting comparative results of different classification techniques, and discuss about several metrics that can be used to assess their performance. Being an initial benchmarking, we expect that the possibility to replicate and outperform the presented results will contribute to further advances in state-of-the-art methods.
ER  -