The DAily Home LIfe Activity Dataset: A High Semantic Activity Dataset for Online Recognition

In this article, we introduce the DAily Home LIfe Activity (DAHLIA) Dataset, a new dataset adapted to the context of smart-home or video-assistance. Videos were recorded in realistic conditions, with 3 KinectTMv2 sensors located as they would be in a real context. The very long-range activities were performed in an unconstrained way (participants received few instructions), and in a continuous (untrimmed) sequence, resulting in long videos (39 min in average per subject). Contrary to previously published databases, in which labeled actions are very short and with low-semantic level, this new database focuses on high-level semantic activities such as ”Preparing lunch” or ”House Working”. As a baseline, we evaluated several metrics on three different algorithms designed for online action recognition or detection.