Counting people in the crowd using social media images for crowd management in city events

City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd management purposes. Previous works proposed a large number of methods to count the crowd using different data in vario...

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Bibliographic Details
Published in:Transportation (Dordrecht) 2021-12, Vol.48 (6), p.3085-3119
Main Authors: Gong, V. X., Daamen, W., Bozzon, A., Hoogendoorn, S. P.
Format: Article
Language:English
Subjects:
Acknowledgment
Cities
Counting
Counting methods
Datasets
Digital media
Economic Geography
Economics
Economics and Finance
Engineering Economics
Face
Face recognition
Imagery
Information management
Innovation/Technology Management
Logistics
Marketing
Mass media
Object recognition
Organization
Pattern recognition
Regional/Spatial Science
Social media
Social networks
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Summary:City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd management purposes. Previous works proposed a large number of methods to count the crowd using different data in various contexts, but no methods proposed using social media images in city events and no datasets exist to evaluate the effectiveness of these methods. In this study we investigate how social media images can be used to estimate the crowd size in city events. We construct a social media dataset, compare the effectiveness of face recognition, object recognition, and cascaded methods for crowd size estimation, and investigate the impact of image characteristics on the performance of selected methods. Results show that object recognition based methods, reach the highest accuracy in estimating the crowd size using social media images in city events. We also found that face recognition and object recognition methods are more suitable to estimate the crowd size for social media images which are taken in parallel view, with selfies covering people in full face and in which the persons in the background have the same distance to the camera. However, cascaded methods are more suitable for images taken from top view with gatherings distributed in gradient. The created social media dataset is essential for selecting image characteristics and evaluating the accuracy of people counting methods in an urban event context.
ISSN:0049-4488
1572-9435
DOI:10.1007/s11116-020-10159-z