RGB-D Human Activity Recognition and Video Database
The availability of low-cost depth cameras has encouraged the computer vision community to investigate depth video as the basis for recognizing actions and activities, with potentially greater accuracy and higher speed than is possible with conventional video.
However, to compare proposed new action recognition algorithms, researchers need a reference set of action footage filmed with depth cameras, to serve as a benchmarking database. ADSC’s benchmark dataset includes registered depth and colour video footage showing people performing activities of daily life, which is essential for several applications, including smart homes and assisted living. This database contains 1189 RGB-D video samples on 12 daily activity categories, collected from 30 subjects.
Human Activity Detection from RGBD Images, Bingbing Ni, Gang Wang, Pierre Moulin. In ICCV workshop on Consumer Depth Cameras for Computer Vision (CDC4CV’11), 2011 [pdf] [database download].