Embedded system for real-time person detecting in infrared images/videos using super-resolution and Haar-like feature techniques

Gilberto Guadalupe Jara Ramos, Juan Carlos Sanchez Garcia, Volodymyr Ponomariov

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4 Citas (Scopus)

Resumen

This paper describes a real time person detection system using near infrared images/videos. This novel system integrates person detection and super resolution algorithms performing person recognition. Additionally, we use a detector Haar-like features and for increasing resolution we use classical algorithms like Nearest neighbor interpolation, Bilineal interpolation and bicubic interpolation. The detector is trained using Adataboost and cascade classifiers and the implementation is performed in the embeded system Raspberry pi2 with the Noir Pi Camera. The implemented embedded system runs at about 20 frames/second.

Idioma originalInglés
Título de la publicación alojada2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781467378390
DOI
EstadoPublicada - 14 dic. 2015
Evento12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015 - Mexico City, México
Duración: 26 oct. 201530 oct. 2015

Serie de la publicación

Nombre2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015

Conferencia

Conferencia12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015
País/TerritorioMéxico
CiudadMexico City
Período26/10/1530/10/15

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