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Automatic Matching of Multimodular Images in Live Golf Environments: An Evaluation of Methods to Estimate a Homography Between Multimodular Images
KTH, School of Computer Science and Communication (CSC).
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Automatisk matchning av multimodulära bilder i direktsändningar av golf (Swedish)
Abstract [en]

This degree project evaluates combinations of well-known state-of-the-art keypoint detectors and descriptors, as well as keypoint matching and robust outlier rejection methods for the purpose of estimating a homography between images produced by two fundamentally different cameras. The evaluation is perfomed on both computational efficiency and matching accuracy of each combination after a series of image deformations have been applied. The results show best performance using Brute Force search with the Hamming distance on keypoint descriptors generated by running the BRISK/BRISK combination and RANSAC for finding the subset to be used in the final homography estimation. If necessary for extra time sensitive applications, using ORB/ORB for keypoint detection and description has been shown to produce largely comparable results at a higher computational efficiency

Abstract [sv]

Det här arbetet evaluerar kombinationer av välkända detektorer och deskriptorer, samt metoder för att matcha dessa och välja ut de bästa för att estimera en homografi mellan två fundamentalt olika kameror. Evalueringen baseras både på tidsåtgång och slutgiltig matchningskvalitet efter en rad bilddeformationer har applicerats. Resultaten visar bäst resultat när en totalsökning med Hammingnormen körs på ett set av punkter funna med hjälp av kombinationen BRISK/BRISK och sedan RANSAC för att hitta det bästa subsetet av dessa för att estimera homografin. Om nödvändigt för extra tidskänsliga applikationer har kombinationen ORB/ORB visat sig prestera i stort sett lika bra och med en ökad effektivitet.

Place, publisher, year, edition, pages
2016.
Keyword [en]
image matching automatic golf detector descriptor computer vision homography
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-190747OAI: oai:DiVA.org:kth-190747DiVA: diva2:952599
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2016-08-18 Created: 2016-08-15 Last updated: 2016-08-18Bibliographically approved

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