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Retail Traffic-Flow Analysis Using a Fast Multi-object Detection and Tracking System

  • Richard Cobos
  • Jefferson Hernandez
  • Andres G. AbadEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1096)

Abstract

Traffic-flow analysis allows to make critical decisions for retail operation management. Common approaches for traffic-flow analysis make use of hardware-based solutions, which have major drawbacks, such as high deployment and maintenance costs. In this work, we address this issue by proposing a Multiple-Object Tracking (MOT) system, following the tracking-by-detection paradigm, that leverages on an ensemble of detectors, each running every f frames. We further measured the performance of our model in the MOT16 Challenge and applied our algorithm to obtain heatmaps and paths for customers and shopping carts in a retail store from CCTV cameras.

Keywords

Multi-object tracking Shopping-carts detection Indoor localization and tracking Kalman filters 

Notes

Acknowledgment

The authors would like to acknowledge the stimulating discussions and help from Victor Merchan, Joo Wang Kim and Ricardo Palacios, as well as Tiendas Industriales Asociadas Sociedad Anonima (TIA S.A.), a leading grocery retailer in Ecuador, for providing funding for this research effort.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Industrial Artificial Intelligence (INARI) Research LabEscuela Superior Politecnica del Litoral (ESPOL)GuayaquilEcuador

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