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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A New Approach for Pedestrian Density Estimation Using Moving Sensors and Computer Vision Sensing the city

Full text
Author(s):
Tokuda, Eric K. [1] ; Lockerman, Yitzchak [2] ; Ferreira, Gabriel B. A. [1] ; Sorrelgreen, Ethan [3] ; Boyle, David [4] ; Cesar-Jr, Roberto M. ; Silva, Claudio T. [2]
Total Authors: 7
Affiliation:
[1] Univ Sao Paulo, Rua Matao 1010, BR-05508090 Sao Paulo, SP - Brazil
[2] NYU, 2 MetroTech Ctr, New York, NY 11201 - USA
[3] Carmera, 1100 NE Campus Pkwy Suite 200, Seattle, WA 98195 - USA
[4] Carmera, 20 Jay St Suite 312, New York, NY 11201 - USA
Total Affiliations: 4
Document type: Journal article
Source: ACM TRANSACTIONS ON SPATIAL ALGORITHMS AND SYSTEMS; v. 6, n. 4 AUG 2020.
Web of Science Citations: 0
Abstract

An understanding of person dynamics is indispensable for numerous urban applications, including the design of transportation networks and planning for business development. Pedestrian counting often requires utilizing manual or technical means to count individuals in each location of interest. However, such methods do not scale to the size of a city and a new approach to fill this gap is here proposed. In this project, we used a large dense dataset of images of New York City along with computer vision techniques to construct a spatio-temporal map of relative person density. Due to the limitations of state-of-the-art computer vision methods, such automatic detection of person is inherently subject to errors. We model these errors as a probabilistic process, for which we provide theoretical analysis and thorough numerical simulations. We demonstrate that, within our assumptions, our methodology can supply a reasonable estimate of person densities and provide theoretical bounds for the resulting error. (AU)

FAPESP's process: 14/24918-0 - Weakly supervised learning for face and person attributes detection
Grantee:Eric Keiji Tokuda
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants