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231224s2017 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2016.2630687
|2 doi
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|a eng
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| 100 |
1 |
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|a Rengarajan, Vijay
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Image Registration and Change Detection under Rolling Shutter Motion Blur
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| 264 |
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|c 2017
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 23.11.2018
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|a Date Revised 23.11.2018
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a In this paper, we address the problem of registering a distorted image and a reference image of the same scene by estimating the camera motion that had caused the distortion. We simultaneously detect the regions of changes between the two images. We attend to the coalesced effect of rolling shutter and motion blur that occurs frequently in moving CMOS cameras. We first model a general image formation framework for a 3D scene following a layered approach in the presence of rolling shutter and motion blur. We then develop an algorithm which performs layered registration to detect changes. This algorithm includes an optimisation problem that leverages the sparsity of the camera trajectory in the pose space and the sparsity of changes in the spatial domain. We create a synthetic dataset for change detection in the presence of motion blur and rolling shutter effect covering different types of camera motion for both planar and 3D scenes. We compare our method with existing registration methods and also show several real examples captured with CMOS cameras
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Rajagopalan, Ambasamudram Narayanan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Aravind, Rangarajan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Seetharaman, Guna
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 39(2017), 10 vom: 03. Okt., Seite 1959-1972
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|g pages:1959-1972
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|u http://dx.doi.org/10.1109/TPAMI.2016.2630687
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