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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Srivastava, Satyam Ng, Ka Ki Delp, Edward J. |
| Copyright Year | 2011 |
| Description | Author affiliation: Video and Image Processing Laboratory (VIPER), School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana, USA (Srivastava, Satyam; Ng, Ka Ki; Delp, Edward J.) |
| Abstract | Behavioral information can be inferred from the trajectory of a rigid object. We propose a method to detect anomalies in the approach of a vehicle by observing the patterns in its velocity and describe methods for more effective analysis of the velocity trajectory. First we define a hypothetical co-ordinate system in which the axes are specified with respect to the road and distances are true ground measurements. In this co-ordinate system the (axial) velocity is a one dimensional quantity. We estimate the “normal” trends in the velocities by activity path modeling after scaling the velocities by the vehicle's average speed. We detect an anomaly if a vehicle's velocity does not fall in the available path models. Finally, we use the shape of the trajectory to determine turns and other significant maneuvers. We also detect an anomaly if a vehicle's velocity falls in a path model which is inconsistent with the shape of its trajectory. We observe that our proposed co-ordinate system also improves trajectory shape analysis by suppressing false turns. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 440632 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781612843483 |
| ISSN | 19457871 |
| e-ISBN | 9781612843506 |
| e-ISBN | 9781612843490 |
| DOI | 10.1109/ICME.2011.6011879 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-11 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Trajectory Vehicles Shape Roads Table lookup Real time systems Object detection |
| Content Type | Text |
| Resource Type | Article |
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