Detecting Nature in Pictures

Bibliographic Details
Main Author: Tiago Miguel Pereira Andrade
Publication Date: 2013
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/10216/68816
Summary: With the advent of large-scale geo-tagged image sharing on the internet, on websites such as Flickr and Panoramio, there are now large sources of data ready to be mined for useful information. Using this data to automatically create a map of man-made and natural areas of our planet, can provide additional knowledge to decision-makers responsible for world-conservation. The problem of determining the degree of naturalness of an image, required to create such a map, can be generalized as a scene classification task. Experiments were performed to better understand the applicability of each of the identified scene classification techniques to perform the distinction between man-made and natural images. Their advantages and limitations, such as their computational costs, are detailed. With careful selection of techniques and their parameters it was possible to build a classifier capable of distinguishing between natural and man-made scenery with high accuracy and that can also process a large amount of pictures within a reasonable time frame.
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spelling Detecting Nature in PicturesEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringWith the advent of large-scale geo-tagged image sharing on the internet, on websites such as Flickr and Panoramio, there are now large sources of data ready to be mined for useful information. Using this data to automatically create a map of man-made and natural areas of our planet, can provide additional knowledge to decision-makers responsible for world-conservation. The problem of determining the degree of naturalness of an image, required to create such a map, can be generalized as a scene classification task. Experiments were performed to better understand the applicability of each of the identified scene classification techniques to perform the distinction between man-made and natural images. Their advantages and limitations, such as their computational costs, are detailed. With careful selection of techniques and their parameters it was possible to build a classifier capable of distinguishing between natural and man-made scenery with high accuracy and that can also process a large amount of pictures within a reasonable time frame.2013-07-122013-07-12T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/68816engTiago Miguel Pereira Andradeinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-27T18:08:55Zoai:repositorio-aberto.up.pt:10216/68816Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T22:38:56.463694Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Detecting Nature in Pictures
title Detecting Nature in Pictures
spellingShingle Detecting Nature in Pictures
Tiago Miguel Pereira Andrade
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short Detecting Nature in Pictures
title_full Detecting Nature in Pictures
title_fullStr Detecting Nature in Pictures
title_full_unstemmed Detecting Nature in Pictures
title_sort Detecting Nature in Pictures
author Tiago Miguel Pereira Andrade
author_facet Tiago Miguel Pereira Andrade
author_role author
dc.contributor.author.fl_str_mv Tiago Miguel Pereira Andrade
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description With the advent of large-scale geo-tagged image sharing on the internet, on websites such as Flickr and Panoramio, there are now large sources of data ready to be mined for useful information. Using this data to automatically create a map of man-made and natural areas of our planet, can provide additional knowledge to decision-makers responsible for world-conservation. The problem of determining the degree of naturalness of an image, required to create such a map, can be generalized as a scene classification task. Experiments were performed to better understand the applicability of each of the identified scene classification techniques to perform the distinction between man-made and natural images. Their advantages and limitations, such as their computational costs, are detailed. With careful selection of techniques and their parameters it was possible to build a classifier capable of distinguishing between natural and man-made scenery with high accuracy and that can also process a large amount of pictures within a reasonable time frame.
publishDate 2013
dc.date.none.fl_str_mv 2013-07-12
2013-07-12T00:00:00Z
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