Image alignment for panorama stitching in sparsely structured environments
| Autor: | Klas Nordberg, Michael Felsberg, Martin Danelljan, Giulia Meneghetti |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Image alignment
Panorama Computer science 0211 other engineering and technologies ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image registration 02 engineering and technology Image stitching Discriminative model Datorseende och robotik (autonoma system) 0202 electrical engineering electronic engineering information engineering Computer vision Computer Vision and Robotics (Autonomous Systems) 021101 geological & geomatics engineering Panorama stitching business.industry Discriminative correlation filters Feature (computer vision) Phase correlation Eye tracking 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Lecture Notes in Computer Science Lecture Notes in Computer Science-Image Analysis Scandinavian Conference on Image Analysis Image Analysis ISBN: 9783319196640 SCIA |
| ISSN: | 0302-9743 1611-3349 |
| Popis: | Panorama stitching of sparsely structured scenes is an open research problem. In this setting, feature-based image alignment methods often fail due to shortage of distinct image features. Instead, direct image alignment methods, such as those based on phase correlation, can be applied. In this paper we investigate correlation-based image alignment techniques for panorama stitching of sparsely structured scenes. We propose a novel image alignment approach based on discriminative correlation filters (DCF), which has recently been successfully applied to visual tracking. Two versions of the proposed DCF-based approach are evaluated on two real and one synthetic panorama dataset of sparsely structured indoor environments. All three datasets consist of images taken on a tripod rotating 360 degrees around the vertical axis through the optical center. We show that the proposed DCF-based methods outperform phase correlation-based approaches on these datasets. VPS |
| Databáze: | OpenAIRE |
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