A Fast-RCNN implementation for human silhouette detection in video sequences

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

Abstract

The intention of this article is to implement a system of detection and segmentation of human silhouettes, the above mentioned tasks present a great challenge in security topics and innovation, in the last years and mainly on automated video surveillance systems, which require understanding the presence and human interaction in video sequences, e.g. Human Computer Interaction (HCI), Human Behaviour comprehension, Human fall detection, among others, but the most important is behavioural biometrics, this paper tackles the common step in these research areas: the Human silhouette extraction through the bounding box. To evaluate the proposed system, standardized databases where used and also proper videos are obtained trying to emulate real-world scenarios, where the quality and the distance are factors that have demonstrated challenges for the detection with computer vision and machine learning.

Original languageEnglish
Title of host publicationKnowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020
EditorsHamido Fujita, Ali Selamat, Sigeru Omatu
PublisherIOS Press BV
Pages65-75
Number of pages11
ISBN (Electronic)9781643681146
DOIs
StatePublished - 15 Sep 2020
Event19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020 - Virtual, Online, Japan
Duration: 22 Sep 202024 Sep 2020

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume327
ISSN (Print)0922-6389

Conference

Conference19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020
Country/TerritoryJapan
CityVirtual, Online
Period22/09/2024/09/20

Keywords

  • Computer vision
  • Human silhouette
  • Image processing
  • Pattern recognition
  • R-CNN
  • Real-Time systems

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