Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Chandu, Eerenti; Vinay Kumar, Kasthuri; Chandra Kumar, Kodavati; Snehith, Raja Venkat Sai; Prathap, Boppuru Rudra Title A name given to the resource Enhancing Video Surveillance for Crime Detection Using Anomaly Detection Techniques Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived AIP Conference Proceedings;Volume;3175;Issue;1;Article No.;20070; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1063/5.0254108" target="_blank" rel="noreferrer noopener">https://doi.org/10.1063/5.0254108</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000450459?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000450459?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chandu E., Department of Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Vinay Kumar K., Department of Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Chandra Kumar K., Department of Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Snehith R.V.S., Department of Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Prathap B.R., Department of Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India Description An account of the resource Security cameras are widely used to detect and prevent crimes, but the number of surveillance videos has increased due to this prevalence. The process of detecting similarities or data points that significantly depart from the norm or expected behavior of a given system is known as anomaly detection. Predictive maintenance, network intrusion detection, and fraud detection are just a few of the areas where anomaly detection is applied. By processing these videos with the help of a suitable machine learning algorithm, unfavorable events can be brought to the attention of experts to manually monitor. Since these unfavorable events are of various types and few in number, this problem can be addressed in the anomaly detection structure. An anomaly detection algorithm has been developed using the UCF-Crime dataset consisting of 1900 surveillance videos of various lengths. In this context, video surveillance refers to observing the scenes of improper human behaviors which are termed as real world anomalies. Depending on the availability of data sets, anomaly detection algorithms can be supervised, unsupervised, or semi- supervised. The quality of the data and the selection of the best algorithms determine how well anomaly detection techniques work. This paper proposes the use of anomaly detection techniques to enhance video surveillance systems for crime detection. By identifying unusual activities in surveillance footage, the system can alert authorities to potential criminal activity and improve overall security measures. The effectiveness of this approach is demonstrated through experiments and analysis of real-world surveillance data. 2025 Author(s). Publisher An entity responsible for making the resource available American Institute of Physics Relation A related resource ISSN: 0094243X; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online