TY  - JOUR
PY  - 2020//
TI  - Improved accuracy of suspicious activity detection in surveillance video
JO  - International journal of engineering and advanced technology
A1  - Gurav, S. S.
A1  - Godbole, B. B.
A1  - Sonale, M. S.
SP  - 267
EP  - 270
VL  - 9
IS  - 3
N2  - 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.     Keywords: Surveillance video, GLCM, Cosine similarity, descriptors, Harris corner, Euclidian distance.<p />  <p>Language: en</p>
LA  - en
SN  - 2249-8958
UR  - http://dx.doi.org/10.35940/ijeat.C4726.029320
ID  - ref1
ER  -