Comparison of Main Approaches for Extracting Behavior Features from Crowd Flow Analysis

Author:

Ebrahimpour ,Wan ,Cervantes ,Luo ,Ullah

Abstract

Extracting features from crowd flow analysis has become an important research challenge due to its social cost and the impact of inadequate planning of high-quality services and security monitoring on the lives of citizens. This paper descriptively reviews and compares existing crowd analysis approaches based on different data sources. This survey provides the fundamentals of crowd analysis and considers three main approaches: crowd video analysis, crowd spatio-temporal analysis, and crowd social media analysis. The key research contributions in each approach are presented, and the most significant techniques and algorithms used to improve the precision of results that could be integrated into solutions to enhance the quality of services in a smart city are analyzed.

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

Reference68 articles.

1. Urban Computing

2. Abnormal Prediction of Dense Crowd Videos by a Purpose–Driven Lattice Boltzmann Model

3. Hajj Pilgrimage Stampede: A Visual Guide to the Fatal Rush Near Meccahttps://www.theguardian.com/world/ng-interactive/2015/sep/24/hajj-pilgrimage-stampede-visual-guide-fatal-crush-mecca

4. China New Year’s Eve Crush: At Least 36 Killed and 47 Injured in Shanghai after ‘Fake Money Thrown from Balcony of Nightclub’https://www.independent.co.uk/news/world/asia/new-year-2015-at-least-35-killed-and-42-injured-in-shanghai-stampede-9952461.html

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