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Smart IoT cameras for crowd analysis based on augmentation for automatic pedestrian detection, simulation and annotation

  • Antoine Rimboux
  • , Rob Dupre
  • , Eldriona Daci
  • , Thomas Lagkas
  • , Panagiotis Sarigiannidis
  • , Paolo Remagnino
  • , Vasileios Argyriou
  • Kingston University
  • Link Campus University
  • University of Sheffield
  • University of Western Macedonia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Smart video sensors for applications related to surveillance and security are IOT-based as they use Internet for various purposes. Such applications include crowd behaviour monitoring and advanced decision support systems operating and transmitting information over internet. The analysis of crowd and pedestrian behaviour is an important task for smart IoT cameras and in particular video processing. In order to provide related behavioural models, simulation and tracking approaches have been considered in the literature. In both cases ground truth is essential to train deep models and provide a meaningful quantitative evaluation. We propose a framework for crowd simulation and automatic data generation and annotation that supports multiple cameras and multiple targets. The proposed approach is based on synthetically generated human agents, augmented frames and compositing techniques combined with path finding and planning methods. A number of popular crowd and pedestrian data sets were used to validate the model, and scenarios related to annotation and simulation were considered.
Original languageEnglish
Title of host publication2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-7281-0570-3
ISBN (Print)978-1-7281-0571-0
DOIs
Publication statusPublished - 19 Aug 2019
Event15th Annual International Conference on Distributed Computing in Sensor Systems (DCOSS) 2019 - Santorini Island, Greece
Duration: 29 May 201931 May 2019

Publication series

NameInternational Conference on Distributed Computing in Sensor Systems (DCOSS)
ISSN (Print)2325-2936
ISSN (Electronic)2325-2944

Conference

Conference15th Annual International Conference on Distributed Computing in Sensor Systems (DCOSS) 2019
Period29/05/1931/05/19

Keywords

  • Computer science and informatics

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