With the increasing of surveillance cameras in modern cities, huge amount of videos can be collected. While there are insufficient human resource for monitoring all the screens at one time.
We are considering how to use techniques of video understanding to detect violent behavior so that it can give a quick alarm in time.
Collected raw surveillance videos from YouTube, sliced them into clips within 5s at 30 fps, and labeled each clip as Violent or Non-Violent Behavior。
Dropped duplicated contents which appear in both training set and validation set.
Finally we got 2000 clips and 300,000 frames as a new data set for real-world violent behavior detection under surveillance camera.
Since all the videos are captured by surveillance cameras in public places, many of them may not have a good imaging quality due to dark environment, fast movement of object, lighting blur, etc. Here are some examples:
- Only part of the person appears in the picture
- Crowds and chaos
- Small object at far distance
- Low resolution
- Transient action
To download the released dataset, please send an e-mail to us ([email protected]) including details of contact information (full name, title, institution, and country) and the purpose for using the dataset. Notes for students: we require your academic supervisor to write this e-mail on your behalf.
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