Embedded polarizing filters to separate diffuse and specular reflection

Co-authors

Laurent Jospin and Gilles Baechler.


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Full text: Arxiv.
Cite: Bibtex.
Code: Will appear shortly.


Abstract

Polarizing filters provide a powerful way to separate diffuse and specular reflection; however, traditional methods rely on several captures and require proper alignment of the filters. Recently, camera manufacturers have proposed to embed polarizing micro-filters in front of the sensor, creating a mosaic of pixels with different polarizations. In this paper, we investigate the

Combining Range and Direction for Improved Localization

Co-authors

Gilles Baechler, Frederike Dümbgen, Golnoosh Elhami, Miranda Krekovic, Robin Scheibler and Martin Vetterli.


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Full text: Infoscience.
Cite: Bibtex.
Code: GitHub.


Abstract

Self-localization of nodes in a sensor network is typically achieved using either range or direction measurements; in this paper, we show that a constructive combination of both improves the estimation. We propose two localization algorithms that make use of the differences between the sensors’ coordinates, or

Sampling at unknown locations: uniqueness and reconstruction under constraints

Co-authors

Golnoosh Elhami, Michalina Pacholska, Benjamín Béjar Haro and Martin Vetterli.


Downloads

Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Infoscience.


Abstract

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is often hopeless. For example, we recently showed that, for polynomial

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