INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
ABNORMAL CROWD BEHAVIOUR DETECTION BASED ON THE HABITAT LOCATION
Authors Name:
V. Deepiga
, Mrs.S.Revathy
Unique Id:
IJSDR1703032
Published In:
Volume 2 Issue 3, March-2017
Abstract:
Crowd density estimation and abnormal crowd behaviour detection have become increasingly important subjects of research in computer vision. Some of the issues in crowd analysis include perspective distortion, occlusions, illumination changes, etc. Crowd density estimation and crowd behaviour detection plays a vital role in security systems, congestion control and public space design. We propose a novel framework for crowd density estimation and abnormal crowd behaviour detection. In crowd density estimation, we propose a novel feature extraction method by combining the texture and pixel features of crowd. These features are then given to a neural network to estimate the level of crowd density and perspective distortion has also been handled. In abnormal crowd behaviour detection, we propose a novel edge based feature points extraction method that eliminates the need to remove the static feature points in the subsequent frames. KLT tracker has been used to track the points and to determine the principal direction of motion of each feature point a direction count algorithm is proposed. The motion attributes such as principal directions, speed are used to model the crowd behaviour based on threshold values. Experimental results show that our proposed method identifies the crowd density level with accuracy 95% and crowd behaviour with accuracy 97%.
Keywords:
Video, Crowd density, MATLAB
Cite Article:
"ABNORMAL CROWD BEHAVIOUR DETECTION BASED ON THE HABITAT LOCATION", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.2, Issue 3, page no.210 - 215, March-2017, Available :http://www.ijsdr.org/papers/IJSDR1703032.pdf
Downloads:
000337064
Publication Details:
Published Paper ID: IJSDR1703032
Registration ID:170119
Published In: Volume 2 Issue 3, March-2017
DOI (Digital Object Identifier):
Page No: 210 - 215
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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