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Facing the differences between Facebook and OpenCV: A facial detection comparison between Open Library Computer Vision and Facebook
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Face detection is used in many different areas and with this thesis

we aim to show the difference between Facebooks face detection soft-ware compared with an open source version from OpenCV. By using

the simplest implementation of OpenCV we want to find out if it is

viable for use in personal applications and be of help for others wanting

to implement face detection. The dataset was meticulously checked to

find the exact number of faces in each image so that the optimal result

is given. The conclusion of this study is that Facebooks algorithm is

better trained and thus has better results, however OpenCV is still a

viable choice for your own applications.

Place, publisher, year, edition, pages
2015.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-166281OAI: oai:DiVA.org:kth-166281DiVA: diva2:810287
Supervisors
Examiners
Available from: 2015-05-28 Created: 2015-05-07 Last updated: 2015-05-28Bibliographically approved

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fulltext(454 kB)485 downloads
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CiteExportLink to record
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Citation style
  • apa
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Language
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Output format
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