We present a computational approach to abnormal visual event detection, which is based on exploring and modeling local motion patterns in a non-linear subspace. We use motion vect...
We present an algorithm for detecting human actions
based upon a single given video example of such actions.
The proposed method is unsupervised, does not require
learning, segm...
We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient ba...
Detecting low-level image features such as edges and ridges with spatial filters is improved if the scale of the features are known a priori. Scale-space representations and wavele...
Video surveillance systems produce huge amounts of data for storage and display. Long-term human monitoring of the acquired video is impractical and ineffective. Automatic abnorma...