A new approach for pedestrian density estimation using moving sensors and computer vision

• Published in: arXiv.org
• Main Authors: Tokuda, Eric K, Lockerman, Yitzchak, Ferreira, Gabriel B A, Sorrelgreen, Ethan, Boyle, David, Cesar-Jr, Roberto M, Silva, Claudio T
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 03.07.2020
• Subjects: Computer Science - Computer Vision and Pattern Recognition; Computer simulation; Computer vision; Counting; Density; Machine learning; Mathematical models; Pedestrians; Planing; Transportation networks

An understanding of pedestrian dynamics is indispensable for numerous urban applications including the design of transportation networks and planing for business development. Pedestrian counting often requires utilizing manual or technical means to count individuals in each location of interest. How...