Type: Dataset
Tags: action recognition, fight detection, video surveillance

title= {Movies Fight Detection Dataset},
author= {Nievas, Enrique Bermejo and Suarez, Oscar Deniz and Garcia, Gloria Bueno and Sukthankar, Rahul},
booktitle= {Computer Analysis of Images and Patterns},
pages= {332--339},
year= {2011},
organization= {Springer},
abstract= {Whereas the action recognition community has focused mostly on detecting simple actions like clapping, walking or jogging, the detection
of fights or in general aggressive behaviors has been comparatively less studied. Such capability may be extremely useful in some video
surveillance scenarios like in prisons, psychiatric or elderly centers or even in camera phones. After an analysis of previous approaches we test the well-known Bag-of-Words framework used for action recognition in the specific problem of fight detection, along with two of the best action descriptors currently available: STIP and MoSIFT. For the purpose of evaluation and to foster research on violence detection in video we introduce a new video database containing 1000 sequences divided in two groups: fights and non-fights. Experiments on this database and another one with fights from action movies show that fights can be detected with near 90% accuracy.
keywords= {action recognition, fight detection, video surveillance},
terms= {},
url= {}

10 day statistics (21 downloads)

Average Time 7 mins, 59 secs
Average Speed 855.79kB/s
Best Time 1 mins, 26 secs
Best Speed 4.77MB/s
Worst Time 20 mins, 01 secs
Worst Speed 341.35kB/s