UCF50 action recognition dataset

[* Glenn Becker]

UCF50 is an action recognition dataset with 50 action categories,
consisting of realistic videos taken from youtube. This dataset is an
extension of YouTube Action dataset which has 11 action categories.
The dataset can be downloaded from the following address:
http://server.cs.ucf.edu/~vision/data/UCF50.rar

Most of the available action recognition datasets are not realistic
and are staged by actors. In our dataset, the primary focus is to
provide the computer vision community with an action recognition
dataset consisting of realistic videos which are taken from youtube.
Our dataset is very challenging due to large variations in camera
motion, object appearance and pose, object scale, viewpoint, cluttered
background, illumination conditions, etc. For all the 50 categories,
the videos are grouped into 25 groups, where each group consists of
more than 4 action clips. The video clips in the same group may share
some common features, such as the same person, similar background,
similar viewpoint, and so on.

UCF50 dataset's 50 action categories collected from youtube are:
Baseball Pitch, Basketball Shooting, Bench Press, Biking, Biking,
Billiards Shot,Breaststroke, Clean and Jerk, Diving, Drumming,
Fencing, Golf Swing, Playing Guitar, High Jump, Horse Race, Horse
Riding, Hula Hoop, Javelin Throw, Juggling Balls, Jump Rope, Jumping
Jack, Kayaking, Lunges, Military Parade, Mixing Batter, Nun chucks,
Playing Piano, Pizza Tossing, Pole Vault, Pommel Horse, Pull Ups,
Punch, Push Ups, Rock Climbing Indoor, Rope Climbing, Rowing, Salsa
Spins, Skate Boarding, Skiing, Skijet, Soccer, Juggling, Swing,
Playing Tabla, TaiChi, Tennis Swing, Trampoline Jumping, Playing
Violin, Volleyball Spiking, Walking with a dog, and Yo Yo.

Please contact Kishore Reddy at kkr...@mail.ucf.edu if you encounter
any problems.