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June 26, 2017 
The U. V. Helava Award

Best Paper 2004


The U.V. Helava Award, sponsored by Elsevier B.V. and Leica Geosystems GIS & Mapping, LLC is a prestigious ISPRS Award, which was established in 1998 to encourage and stimulate submission of high quality scientific papers by individual authors or groups to the ISPRS Journal, to promote and advertise the Journal, and to honour the outstanding contributions of Dr. Uuno V. Helava to research and development in Photogrammetry and Remote Sensing.

 

The Award is presented to authors of the best paper, written in English and published exclusively in the ISPRS Journal during the fouryear period from January of a Congress year, to December of the year prior to the next Congress. The Award consists of a monetary grant of SFr. 10,000 and a plaque. A five-member jury, comprising experts of high scientific standing, whose expertise covers the main topics included in the scope of the Journal, evaluates the papers. For each year of the four-year evaluation period, the best paper is selected, and among these four papers, the one to receive the U.V. Helava Award.

 

The third U.V. Helava Award will be presented at the 21th ISPRS Congress, Beijing, 3-11 July 2008. The five-member jury appointed by the ISPRS Council evaluated the 25 papers of Vol. 59 (2004) and announced its decision for the Best Paper. The winner of the 2004 Best Paper is:

 

external link  A layered stereo matching algorithm using image segmentation and global visibility constraints

by Michael Bleyer1, Margrit Gelautz1

(1)Interactive Media Systems Group, Institute for Software Technology and Interactive Systems, Vienna University of Technology, Favoritenstrasse 9-11/188/2, A-1040 Vienna, Austria

 

Michael Bleyer Margrit Gelautz
Michael Bleyer Margrit Gelautz

 

 

Jury's rationale for the paper selection

The problem of (stereo) matching is of broad interest to image processing, and of course especially photogrammetry and remote sensing. This paper - to the jury's knowledge - is the first one to handle planar patches when deriving dense stereo from two images and at the same time performs an objective evaluation using the Middlebury test data set. The theoretically sound techniques published up to now cannot deal with that situation rigorously. Everybody developing a stereo algorithm trying to cope with unstructured scene patches should read this paper. The ideas are innovative, well described and critically analysed.

 

On behalf of the ISPRS and the U.V. Helava Award jury, I would like to congratulate the authors for this distinction and thank them for their contribution. I would also like to thank the sponsors of the Award, and the jury members for their thorough evaluations.

 

George Vosselman
Editor-in-Chief
ISPRS Journal of Photogrammetry and Remote Sensing