Version 1
: Received: 9 August 2020 / Approved: 19 August 2020 / Online: 19 August 2020 (07:49:37 CEST)
How to cite:
Siraj, M. Beyond Tracking in Crowd: Analyzing Crowd based on Physical Characteristics. Preprints2020, 2020080396. https://doi.org/10.20944/preprints202008.0396.v1
Siraj, M. Beyond Tracking in Crowd: Analyzing Crowd based on Physical Characteristics. Preprints 2020, 2020080396. https://doi.org/10.20944/preprints202008.0396.v1
Siraj, M. Beyond Tracking in Crowd: Analyzing Crowd based on Physical Characteristics. Preprints2020, 2020080396. https://doi.org/10.20944/preprints202008.0396.v1
APA Style
Siraj, M. (2020). Beyond Tracking in Crowd: Analyzing Crowd based on Physical Characteristics. Preprints. https://doi.org/10.20944/preprints202008.0396.v1
Chicago/Turabian Style
Siraj, M. 2020 "Beyond Tracking in Crowd: Analyzing Crowd based on Physical Characteristics" Preprints. https://doi.org/10.20944/preprints202008.0396.v1
Abstract
The safety of people is an important phenomenon nowadays. This importance arises due to the crowded places including subway station, universities, colleges, airport, shopping mall and square, and city squares. Therefore, the development of an effective system based on physical characteristics of crowd layout is of significant demand. In this paper, we proposed a novel automated and intelligent systems for crowd event analysis based on a set of physical elements. For this purpose, we take into account optical flow and spatial-time gradient, contour features, and Gaussian processes. Our method combine these characteristics into a unique model to deal with the challenging problem of crowd event analysis. For evaluating our proposed method, we consider a benchmark dataset and a number of different performance metrics. These analysis demonstrate the robustness and effectiveness of our proposed method.
Keywords
crowd analysis; tracking; people safety; crowd features; localized features
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
