Many problems in the field of automatic video surveillance exists today. Some have yet to be overcome. One of these problems is how a computer system automatically can determine if a situation should cause an alarm or not. To resolve this problem, the use of Case-based reasoning (CBR) is proposed. CBR is a technique that allows a system to reason about different situations and to learn from them. The aim is to produce a system that utilizes these abilities. The system should learn to recognize the situations that causes different alarms. When a situation is recognized and categorized, these false alarms can be completely avoided. This master thesis explains and shows the advantages of using such a system together with advanced image processing techniques.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ntnu-15843 |
| Date | January 2006 |
| Creators | Aasen, Thomas Aron |
| Publisher | Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, Institutt for datateknikk og informasjonsvitenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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