Name
Abstract | ||
|---|---|---|
The work presented in this paper addresses the application of new technologies to the task of intruder monitoring. It presents an innovative Machine Vision application to detect and track a person in a Closed Circuit Television System (CCTV) identifying suspicious activity. Neural Network techniques are applied to identify suspicious activities from the trajectory path, speed, direction and risk areas for a person in a scene, as well as human posture. Results correlate well with operator determining suspicious activity. The automated system presented assists an operator to increase reliability and to monitor large numbers of surveillance cameras. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-04592-9_62 | KES (2) |
Keywords | Field | DocType |
automated system,neural network technique,suspicious activity,human posture,new technology,closed circuit television system,automatic intruder detection,large number,machine vision application,intruder monitoring,risk area,innovative machine vision application,machine vision,neural network,image processing | Computer vision,Machine vision,Computer science,Image processing,Emerging technologies,Operator (computer programming),Artificial intelligence,Artificial neural network,Trajectory | Conference |
Volume | ISSN | Citations |
5712 | 0302-9743 | 2 |
PageRank | References | Authors |
0.51 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hernando Fernandez-Canque | 1 | 8 | 5.07 |
| Sorin Hintea | 2 | 14 | 10.58 |
| John Freer | 3 | 2 | 0.51 |
| Ali Ahmadinia | 4 | 499 | 50.81 |