by Guan, S and Klette, R
Abstract:
The history of stereo analysis of pairs of images dates back more than one hundred years, but stereo analysis of image stereo sequences is a fairly recent subject. Sequences allow time-propagation of results, but also come with particular characteristics such as being of lower resolution, or with less contrast. This article discusses the application of belief propagation (BP), which is widely used for solving various low-level vision problems, for the stereo analysis of night-vision stereo sequences. For this application it appears that BP often fails on the original frames for objects with blurry borders (trees, clouds, …). In this paper, we show that BP leads to more accurate stereo correspondence results if it is applied on edge images, where we have decided for the Sobel edge operator, due to its time efficiency. We present the applied algorithm and illustrate results (without, or with prior edge processing) on seven, geometrically rectified night-vision stereo sequences (provided by Daimler research, Germany). © 2008 Springer-Verlag Berlin Heidelberg.
Reference:
Belief-propagation on edge images for stereo analysis of image sequences (Guan, S and Klette, R), In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 4931 LNCS, 2008.
Bibtex Entry:
@inproceedings{guan2008belief-propagationsequences,
author = "Guan, S and Klette, R",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "291--302",
title = "Belief-propagation on edge images for stereo analysis of image sequences",
volume = "4931 LNCS",
year = "2008",
abstract = "The history of stereo analysis of pairs of images dates back more than one hundred years, but stereo analysis of image stereo sequences is a fairly recent subject. Sequences allow time-propagation of results, but also come with particular characteristics such as being of lower resolution, or with less contrast. This article discusses the application of belief propagation (BP), which is widely used for solving various low-level vision problems, for the stereo analysis of night-vision stereo sequences. For this application it appears that BP often fails on the original frames for objects with blurry borders (trees, clouds, ...). In this paper, we show that BP leads to more accurate stereo correspondence results if it is applied on edge images, where we have decided for the Sobel edge operator, due to its time efficiency. We present the applied algorithm and illustrate results (without, or with prior edge processing) on seven, geometrically rectified night-vision stereo sequences (provided by Daimler research, Germany). © 2008 Springer-Verlag Berlin Heidelberg.",
doi = "10.1007/978-3-540-78157-8_22",
isbn = "3540781560",
isbn = "9783540781561",
issn = "0302-9743",
eissn = "1611-3349",
keyword = "Belief propagation",
keyword = "Image sequence analysis",
keyword = "Sobel operator",
keyword = "Stereo analysis",
language = "eng",
}