Stop the Bus!: computer vision for automatic recognition of urban bus lines

In the present work, the problem of the detection and the recognition of bus line numbers of public transport in the city of C ordoba is addressed, using images obtained by standard mobile devices. The goal of this project is the exploitation of computer vision techniques and the analysis of images...

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Detalles Bibliográficos
Autores principales: Maina, Hernán J., Sánchez, Jorge A.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2020
Materias:
Ciencias Informáticas
Computer vision
Object detection
Text recognition
Text detection
Buses
Visual impairment
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/114923
http://49jaiio.sadio.org.ar/pdfs/asai/ASAI-10.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-114923
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Computer vision
Object detection
Text recognition
Text detection
Buses
Visual impairment
spellingShingle Ciencias Informáticas
Computer vision
Object detection
Text recognition
Text detection
Buses
Visual impairment
Maina, Hernán J.
Sánchez, Jorge A.
Stop the Bus!: computer vision for automatic recognition of urban bus lines
topic_facet Ciencias Informáticas
Computer vision
Object detection
Text recognition
Text detection
Buses
Visual impairment
description In the present work, the problem of the detection and the recognition of bus line numbers of public transport in the city of C ordoba is addressed, using images obtained by standard mobile devices. The goal of this project is the exploitation of computer vision techniques and the analysis of images for the generation of a tool that potentially allows people with visual impairments to be assisted. To achieve this, a modular architecture based on object detectors and optical character recognition is presented and evaluated, mainly constituted by two stages: one for the detection buses, based on the SSD-MobileNet object detection model; and another, responsible for line number recognition, where the EAST and OCR-Tesseract text detection and recognition models are tested, respectively. With a maximum probability of recognition of 62% in a simple image; over an image sequence, the nal system was able to correctly recognize the bus line in 72% of the cases tested.
format Objeto de conferencia
Objeto de conferencia
author Maina, Hernán J.
Sánchez, Jorge A.
author_facet Maina, Hernán J.
Sánchez, Jorge A.
author_sort Maina, Hernán J.
title Stop the Bus!: computer vision for automatic recognition of urban bus lines
title_short Stop the Bus!: computer vision for automatic recognition of urban bus lines
title_full Stop the Bus!: computer vision for automatic recognition of urban bus lines
title_fullStr Stop the Bus!: computer vision for automatic recognition of urban bus lines
title_full_unstemmed Stop the Bus!: computer vision for automatic recognition of urban bus lines
title_sort stop the bus!: computer vision for automatic recognition of urban bus lines
publishDate 2020
url http://sedici.unlp.edu.ar/handle/10915/114923
http://49jaiio.sadio.org.ar/pdfs/asai/ASAI-10.pdf
work_keys_str_mv AT mainahernanj stopthebuscomputervisionforautomaticrecognitionofurbanbuslines
AT sanchezjorgea stopthebuscomputervisionforautomaticrecognitionofurbanbuslines
bdutipo_str Repositorios
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