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High accuracy stereo Structure from Motion through symmetry cost functions: Using cost functions with symmetry terms for high accuracy relative motion estimation
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Nogrann estimering av relativ stereokamerarörelse genom symmetri i kostnadsfunktioner (Swedish)
Abstract [en]

A large effort, in the field of Computer Vision in general and Structurefrom Motion (SfM) in particular, has previously b een put into developing algorithms for estimating camera p ose and triangulate 3D features. Many of thesealgorithms however are based up on maximum p osterior likeliho o d cost functions which are efficient in terms of time consumption rather than in accuracy.The implementations are thus based on a simplified mo del in order to makethe algorithm more efficient. This pro ject aimed to lo ok at a particular problem, stereo cameras with approximately known relative motion, and the goalwas to develop a more accurate cost function. The algorithms presented usesthe symmetry of the measured noise in order to pro duce an estimated relativemotion which outp erforms the least square(L2) method with outlier rejection.The project did include both synthetic and real test data sets. The project wasdone at the request of a company and the testing sets were based on typicalproperties of a projectile tracking system used by the company.

Abstract [sv]

Ett vanligt forskningsområde inom Structure from Motion (SfM) är att estimera den relativa rörelsen mellan kameror. Många av dessa algoritmer förenklarden använda mo dellen för att sänka tidskonsumtionen av pro cessen iställetför att öka precisionen. Detta pro jekt hade som mål att undersöka ett sp ecifikt problem, stereo kameror med relativ rörelse där den relativa rörelsen varapproximativt känd, samt utveckla en mer realistisk kostnadsfunktion för utvärdering ur ett efterhand maximal sannolikhetsp ersp ektiv. Algoritmen sompresenteras i rapp orten använder symmetrin i bruset för att pro ducera en estimering av den relativa rörelsen som överträffar minsta kvadratmeto der (L2)med förkastning av felaktigt ihopkopplade bildpunkter. Projektet inkluderadebåde verkliga såväl som syntetiska dataset. Projektet utfördes på begäran avett företag och de syntetiska dataseten var baserade på typiska egenskaper iföretagets projektilspårningssystem.

Place, publisher, year, edition, pages
2014.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-155888OAI: oai:DiVA.org:kth-155888DiVA: diva2:763219
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Available from: 2015-05-28 Created: 2014-11-13 Last updated: 2015-05-28Bibliographically approved

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CiteExportLink to record
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