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Relative camera pose estimation using convolutional neural networks

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoAdvanced Concepts for Intelligent Vision Systems - 18th International Conference, ACIVS 2017, Proceedings
KustantajaSpringer Verlag
Sivut675-687
Sivumäärä13
ISBN (painettu)9783319703527
DOI - pysyväislinkit
TilaJulkaistu - 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Advanced Concepts for Intelligent Vision Systems -
Kesto: 1 tammikuuta 1900 → …

Julkaisusarja

NimiLecture Notes in Computer Science
Vuosikerta10617
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Conference

ConferenceInternational Conference on Advanced Concepts for Intelligent Vision Systems
Ajanjakso1/01/00 → …

Tiivistelmä

This paper presents a convolutional neural network based approach for estimating the relative pose between two cameras. The proposed network takes RGB images from both cameras as input and directly produces the relative rotation and translation as output. The system is trained in an end-to-end manner utilising transfer learning from a large scale classification dataset. The introduced approach is compared with widely used local feature based methods (SURF, ORB) and the results indicate a clear improvement over the baseline. In addition, a variant of the proposed architecture containing a spatial pyramid pooling (SPP) layer is evaluated and shown to further improve the performance.

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