A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
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 vectors extracted over a Region of Interest (ROI) as features and a non-linear, graph-based manifold learning algorithm coupled with a supervised novelty classifier to label segments of a video sequence. Given a small sample of annotated normal motion vectors, the non-linear detector ranks segments in a sequence as adoi:10.1016/j.neucom.2009.10.028 fatcat:if6u5a3ag5ffvaegl2vdvxhzkm