
By Sergey V. Sai, Ilya S. Sai, Nikolay Yu. Sorokin (auth.), Jacques Blanc-Talon, Don Bone, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
ISBN-10: 3642176879
ISBN-13: 9783642176876
ISBN-10: 3642176887
ISBN-13: 9783642176883
This quantity collects the papers approved for presentation on the twelfth Int- nationwide convention on “Advanced thoughts for clever imaginative and prescient structures” (ACIVS 2010). Following the ?rst assembly in Baden-Baden (Germany) in 1999, whichwaspartofalargemulticonference,theACIVSconferencethendeveloped into an autonomous scienti?c occasion and has ever considering maintained the culture of being a unmarried song convention. ACIVS 2010 attracted computing device scientists from 29 di?erent international locations, often from Europe, Australia, and america, but additionally from Asia. even supposing ACIVS is a convention on all parts of photo and video processing, submissions are likely to assemble inside of yes significant ?elds of curiosity. This 12 months 3D and intensity processing and desktop imaginative and prescient and surveillance have been well known subject matters. Noteworthy are the becoming variety of papers relating to theoretical devel- ments. we want to thank the invited audio system Mubarak Shah (University of primary Florida), Richard Kleihorst (VITO, Belgium), Richard Hartley (A- tralian nationwide University), and David Suter (Adelaide collage) for his or her beneficial contributions.
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Extra info for Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010, Sydney, Australia, December 13-16, 2010, Proceedings, Part I
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ACIVS 2010, Part I, LNCS 6474, pp. 30–37, 2010. c Springer-Verlag Berlin Heidelberg 2010 Toward the Detection of Urban Infrastructure’s Edge Shadows 31 urban infrastructure may be considerably wider. A survey of different approaches can be found in [7]. Much work has been done in the analysis of aerial images to estimate changes [11], segment [12], or recognize [8] buildings. In these cases, there is the significant difficulty that images are captured from different positions and different times, thus making it harder to use the simplification provided by the use of a fixed camera.
The database and the method are made publicly available2 . e. the entropy-based approach [11]. pl/~ visible 26 ´ A. Sluzek and M. Paradowski The approach has been tested on our database using publicly available executables3 . However, the achieved results are rather poor since the method is able to find only a few from over a thousand correct matches. Because of lack of other alternatives, we have used our affine-based methods, [18,17], as the references. These methods have high precision (both in terms of the area and object aspects) but their recall is lower.
The problem can be specified as follows: Given two random images I and J , identify in them pairs of near-duplicate image fragments. The term ”near-duplicate fragments” refers to unspecified fragments of (almost) identical objects. However, the visual appearances of those objects may differ because of different scene and camera settings, photometric conditions, digitization parameters and possibly because of certain natural deformations. Image matching based on local features (keypoints are the most typical example of such features) is a popular approach.
Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010, Sydney, Australia, December 13-16, 2010, Proceedings, Part I by Sergey V. Sai, Ilya S. Sai, Nikolay Yu. Sorokin (auth.), Jacques Blanc-Talon, Don Bone, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
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