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

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaKnowledge 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
EditoresHamido Fujita, Ali Selamat, Sigeru Omatu
EditorialIOS Press BV
Páginas65-75
Número de páginas11
ISBN (versión digital)9781643681146
DOI
EstadoPublicada - 15 sep. 2020
Evento19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020 - Virtual, Online, Japón
Duración: 22 sep. 202024 sep. 2020

Serie de la publicación

NombreFrontiers in Artificial Intelligence and Applications
Volumen327
ISSN (versión impresa)0922-6389
ISSN (versión digital)1879-8314

Conferencia

Conferencia19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020
País/TerritorioJapón
CiudadVirtual, Online
Período22/09/2024/09/20

Huella

Profundice en los temas de investigación de 'A Fast-RCNN implementation for human silhouette detection in video sequences'. En conjunto forman una huella única.

Citar esto