Intelligent Video Surveillance Techniques to Detect Suspicious Human Activities: A Critical Review
Download| Volume 2 Issue 2 2021 | |
|---|---|
| Author(s): |
Asad Hameed Soomro
Noor Ahmed Shaikh
Razia Zia
Samar Abbas Mangi Rafaqat Hussain Arain |
| Abstract | Smart video surveillance systems have grown tremendously for providing security to sensitive places. These intelligent systems are integrated with advanced Artificial intelligence and Deep Neural Network algorithms to automatically detect suspicious and non-suspicious activities of humans. In this scenario, one of the most challenging tasks is seeing and recognizing suspicious activity in real-time. This study results from a comparative analysis of fragments extracted from a survey of 42 publications accessible at IEEE, Springer, and Elsevier online repositories, carried out to comprehend suspicious activity detection strategies, which resulted in an exhaustive comparison of several proposed methodologies. Many technologies, mainly based on intelligent approaches such as Neural Systems, Support Vector Machines, Saliency map features, and so on, have evolved as the basis for intelligence in such systems. The review’s results are given in the form of techniques and approaches used to solve research challenges, .and the study concludes with a road map for future research |
| Keywords | Intelligence Video Surveillance, Object Detection, Object Classification, Artificial Intelligence, Deep Neural Network, Suspicious Activity Detection |
| Year | 2021 |
| Volume | 2 |
| Issue | 2 |
| Type | Research paper, manuscript, article |
| Recognized by | Higher Education Commission of Pakistan, HEC | Category | Y | Journal Name | ILMA Journal of Technology & Software Management | Publisher Name | ILMA University | Jel Classification | -- | DOI | - | ISSN no (E, Electronic) | 2709-2240 | ISSN no (P, Print) | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Manuscript Processing | Blind Peer Reviewed | Format | Paper Link | https://ijtsm.ilmauniversity.edu.pk/arc/Vol2/i2/pdf/3.pdf | Page | 14-22 |