DAHLIA (DAily Human Life Activity)

DAHLIA dataset [1] is devoted to human activity recognition, which is a major issue for adapting smart-home services such as user assistance. DAHLIA has been realized in Mobile Mii Platform by CEA LIST, and has been partly supported by ITEA 3 Emospaces Project (https://itea3.org/project/emospaces.html)

Videos were recorded in realistic conditions, with 3 Kinect v2 sensors located as they would be in a real context. The long-range activities were performed in an unconstrained way (participants received only few instructions), and in a continuous (untrimmed) sequence, resulting in long videos (40 min in average per subject). Contrary to previously published databases, in which labeled actions are very short and have low-semantic level, this new database focuses on high-level semantic activities such as « Preparing lunch » or « House Working ».

[1] G. Vaquette, A. Orcesi, L. Lucat and C. Achard, "The DAily Home LIfe Activity Dataset: A High Semantic Activity Dataset for Online Recognition," 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), 2017, pp. 497-504, doi: 10.1109/FG.2017.67.