TY  - JOUR
T1  - Distance and Speed Based Anomaly Detection in Human Crowd Movement
AU - Sharma, Sanchit AU - Sharma, Anshul AU - Ojha, Nitish 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 21
SP  - 5467
EP  - 5472
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.5467.5472
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.5467.5472
KW  - Anomaly detection
KW  -crowded scenes
KW  -video surveillance
KW  -crowd motion
KW  -crowd behaviour
KW  -social constrain
AB  - In this study, we are trying to recognize the irregular structure and vulnerable movement of people
in the crowd to detect any anomaly in the situation by the movement of segmented particles. To accomplish
this we are using a particle structure group in the image and observing its movement with the movement of the
people. As the people move the particle density contract or expands according to the movement and speed of
movement. The link between the contractions or expansion is mapped in the original image. When the
recognized movement is too fast from the group of particles and if we can identify the person, we consider it
a vulnerable object. These tests provide us with the modern analysis of too fast moving people in the crowd
to recognize the hazardous situation. The examinations demonstrate that the proposed technique catches the
progression of the group conduct effectively. In expansion, we have demonstrated that the social constrain
approach beats comparative methodologies in light of immaculate optical stream.
ER  -