Computational Intelligence for Detecting Pedestrian Movement Patterns

2019 ◽  
pp. 148-163
Author(s):  
Juan P. Chavat ◽  
Sergio Nesmachnow
Keyword(s):  
Computational Intelligence ◽  
Movement Patterns ◽  
Pedestrian Movement

scholarly journals Active Safety System for Urban Environments with Detecting Harmful Pedestrian Movement Patterns Using Computational Intelligence

2020 ◽  
Vol 10 (24) ◽  
pp. 9021
Author(s):  
Juan Chavat ◽  
Sergio Nesmachnow ◽  
Andrei Tchernykh ◽  
Vladimir Shepelev
Keyword(s):  
Image Processing ◽  
Object Tracking ◽  
Real Time ◽  
Computational Intelligence ◽  
Movement Patterns ◽  
Movement Pattern ◽  
Urban Environments ◽  
Pattern Detection ◽  
Real Time System ◽  
Pedestrian Movement

This article presents a system for detecting pedestrian movement patterns in urban environments, by applying computational intelligence methods for image processing and pattern detection. The proposed system is capable of processing multiple images and video sources in real-time. Furthermore, it has a flexible design, as it is based on a pipes and filters architecture that makes it easy to evaluate different computational intelligence techniques to address the subproblems involved in each stage of the process. Two main stages are implemented in the proposed system: the first stage is in charge of extracting relevant features of the processed images, by applying image processing and object tracking, and the second stage is responsible for the patterns detection. The experimental analysis of the proposed system was performed over more than 1450 problem instances, using PETS09-S2L1 videos, and the results were compared with part of the Multiple Object Tracking Challenge benchmark results. Experiments covered the two main stages of the system. Results indicate that the proposed system is competitive yet simpler than other similar software methods. Overall, this article provides the theoretical frame and a proof of concept needed for the implementation of a real-time system that takes as input a group of image sequences, extracts relevant features, and detects a set of predefined patterns. The proposed implementation is a reliable proof of the viability of building pedestrian movement pattern detection systems.

scholarly journals Land-Use, Street Configuration and Pedestrian Volume: The Case of a Historic Town, Mymensingh, Bangladesh

2018 ◽  
Vol 15 ◽  
pp. 137-154
Author(s):  
Naimul Aziz
Keyword(s):  
Land Use ◽  
Space Syntax ◽  
Movement Patterns ◽  
Land Uses ◽  
Land Use Pattern ◽  
Pedestrian Movement ◽  
Two Factors ◽  
Use Pattern ◽  
Street Segments

This study explores the relative connections among pedestrian movement patterns, land use and street configuration by analyzing the pedestrian volume, existing land use pattern as well as the street configuration in different streets of Mymensingh. Mymensingh is a historic town of Bangladesh which was established by the British Colonists in more than 200 years ago along the river Brahmaputra. The street patterns of Mymensingh is very unique as it was developed by the fusion of the streets made by British Colonists and the narrow streets made by the local inhabitants. By using the method of Space Syntax the configurational values of street segments are compared with the corresponding pedestrian counts. The study result shows that the correlation is very poor within this two factors as commercial land uses affects the pedestrians more.

Long-range dependence and time-clustering behavior in pedestrian movement patterns in stampedes: The Love Parade case-study

2017 ◽  
Vol 469 ◽  
pp. 265-274 ◽  
Author(s):  
Liping Lian ◽  
Weiguo Song ◽  
Yuen Kwok Kit Richard ◽  
Jian Ma ◽  
Luciano Telesca
Keyword(s):  
Long Range ◽  
Movement Patterns ◽  
Long Range Dependence ◽  
Pedestrian Movement ◽  
Clustering Behavior

Urban Rhode Island Coyotes: Environmental effects on movement patterns

2012 ◽  
Author(s):  
Kathryn Kalafut ◽  
Numi Mitchell ◽  
Wendy Finn
Keyword(s):  
Rhode Island ◽  
Environmental Effects ◽  
Movement Patterns
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