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Displaying 1-6 out of 6 total
USAC: A Universal Framework for Random Sample Consensus
IEEE Transactions on Pattern Analysis and Machine Intelligence
By Rahul Raguram,Ondrej Chum,Marc Pollefeys,Jiri Matas,Jan-Michael Frahm
Issue Date:August 2013
A computational problem that arises frequently in computer vision is that of estimating the parameters of a model from data that have been contaminated by noise and outliers. More generally, any practical system that seeks to estimate quantities from noisy...
On the Privacy Risks of Virtual Keyboards: Automatic Reconstruction of Typed Input from Compromising Reflections
IEEE Transactions on Dependable and Secure Computing
By Rahul Raguram,Andrew M. White,Yi Xu,Jan-Michael Frahm,Pierre Georgel,Fabian Monrose
Issue Date:May 2013
We investigate the implications of the ubiquity of personal mobile devices and reveal new techniques for compromising the privacy of users typing on virtual keyboards. Specifically, we show that so-called compromising reflections (in, for example, a victim...
RECON: Scale-adaptive robust estimation via Residual Consensus
Computer Vision, IEEE International Conference on
By Rahul Raguram,Jan-Michael Frahm
Issue Date:November 2011
In this paper, we present a novel, threshold-free robust estimation framework capable of efficiently fitting models to contaminated data. While RANSAC and its many variants have emerged as popular tools for robust estimation, their performance is largely d...
Efficient Generation of Multi-perspective Panoramas
3D Imaging, Modeling, Processing, Visualization and Transmission, International Conference on
By Enliang Zheng,Rahul Raguram,Pierre Fite-Georgel,Jan-Michael Frahm
Issue Date:May 2011
In this paper, we present an efficient technique for generating multi-perspective panoramic images of long scenes. The input to our system is a video sequence captured by a moving camera navigating through a long scene, and our goal is to efficiently gener...
Computing iconic summaries of general visual concepts
Computer Vision and Pattern Recognition Workshop
By Rahul Raguram, Svetlana Lazebnik
Issue Date:June 2008
This paper considers the problem of selecting iconic images to summarize general visual categories. We define iconic images as high-quality representatives of a large group of images consistent both in appearance and semantics. To find such groups, we perf...
Improved Resolution Scalability for Bi-Level Image Data in JPEG2000
Data Compression Conference
By Rahul Raguram, Michael W. Marcellin, Ali Bilgin
Issue Date:March 2007
In this paper, we address issues regarding bi-level image compression using JPEG2000. While JPEG2000 is designed to compress both bi-level and continuous tone imagery using a single unified framework, there exist significant limitations with respect to its...
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