Human path classifier architecture
Many surveillance systems today provide only a passive form of site monitoring. Extensive video records may be kept to help find the instigator of criminal activities after the crime has been committed but preventive measures require human involvement. In addition, there is a need for large amounts...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Book Chapter |
| Language: | English |
| Published: |
IIUM Press
2011
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/21651/1/Chapter_18.pdf http://irep.iium.edu.my/21651/ http://rms.research.iium.edu.my/bookstore/default.aspx |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Islam Antarabangsa Malaysia |
| Language: | English |
| Summary: | Many surveillance systems today provide only a passive form of site monitoring. Extensive video records may be kept to help find the instigator of criminal activities after the crime has been committed but preventive measures require human involvement. In addition, there is a need for large amounts of data storage to keep up to several large volumes of video streams that may be needed for later analysis. However, monitoring and storage space are not the only concerns. Behavioral analysis itself can be applied to numerous features extracted from video sequences including path detection and other aspects of human behaviour. Up till now, path classification has been carried out mainly using Boolean logic and allows only the identification of unusual paths, and not the extent to which they are deviant from usual paths. This chapter reports on the results to solve this problem with a fuzzy inference approach to
classify paths into different categories |
|---|