Human activities dataset and the ICPR 2012 human activities recognition and localization competition

We describe the LIRIS human activities dataset, the dataset used for the ICPR 2012 human activities recognition and localization competition. In contrast to previous competitions and existing datasets, the tasks focus on complex human behavior involving several people in the video at the same time, on actions involving several interacting people and on human-object interactions. The goal is not only to classify activities, but also to detect and to localize them. The dataset has been shot with two different cameras: a moving camera mounted on a mobile robot delivering grayscale videos in VGA resolution and depth images from a consumer depth camera (Primesense/MS Kinect); and a consumer camcorder delivering color videos in DVD resolution.

[1]  Barbara Caputo,et al.  Recognizing human actions: a local SVM approach , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[2]  Jean-Michel Jolion,et al.  Object count/area graphs for the evaluation of object detection and segmentation algorithms , 2006, International Journal of Document Analysis and Recognition (IJDAR).

[3]  Ronen Basri,et al.  Actions as Space-Time Shapes , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Christopher Joseph Pal,et al.  Activity recognition using the velocity histories of tracked keypoints , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[5]  Cordelia Schmid,et al.  Actions in context , 2009, CVPR.

[6]  Larry S. Davis,et al.  AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video , 2011, AVSS.