5566568
doi
10.35940/ijeat.C4726.029320
oai:zenodo.org:5566568
Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)
Publisher
B. B. Godbole
Professor, Department of Electronics, Karmaveer Bhaurao Patil,College of Engineering & Polytechnic, Satara, Maharashtra, India.
M. S. Sonale
Department of E&TC, Sharad Institute of Technology, College of Engineering Yadrav, Ichalkaranji, Maharashtra, India.
Improved Accuracy of Suspicious Activity Detection in Surveillance Video
S. S. Gurav
Assistant Professor, Department of E&TC, Sharad Institute of Technology, College of Engineering Yadrav, Ichalkaranji, Maharashtra, India.
issn:2249-8958
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Surveillance video, GLCM, Cosine similarity, descriptors, Harris corner, Euclidian distance.
<p>Suspicious activity detection from surveillance video is the main objective of the work presented in this paper. The method developed consist of various stages of suspicious frame detection, and verifying the frame for suspicious activity related analysis of human movements within obtained set of suspicious frames. The method consist of GLCM feature extraction which constitutes the features such as energy, prominence, contrast, entropy, homogeneity type of features and matching using Euclidian distance along with descriptor features obtained by using Harris corner features and cosine similarity index estimation. The successful suspicious activity detection rate is analyzed which shows better performance and time saving method while analyzing large surveillance video dataset.</p>
Zenodo
2020-02-29
info:eu-repo/semantics/article
5566567
1636972151.448136
336611
md5:d1a6e816ac40b96fe8b2c392d163f9bf
https://zenodo.org/records/5566568/files/C4726029320 (1).pdf
public
2249-8958
Is cited by
issn
International Journal of Engineering and Advanced Technology (IJEAT)
9
3
267-270
2020-02-29