By Prarthana Shrestha, Hans Weda, Mauro Barbieri, Peter H. N. de With (auth.), Jacques Blanc-Talon, Don Bone, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
This booklet constitutes the refereed complaints of the twelfth foreign convention on complex recommendations for clever imaginative and prescient platforms, ACIVS 2010, held in Changchun, China, in August 2010. The seventy eight revised complete papers offered have been conscientiously reviewed and chosen from a hundred and forty four submissions. The papers are geared up in topical sections on photo processing and research; segmentation and aspect detection; 3D and intensity; algorithms and optimizations; video processing; surveillance and digicam networks; computer imaginative and prescient; distant sensing; and popularity, type and monitoring.
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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 II
Mappings that relate the spatial coordinates in matched images). Typical geometric models used in state-of-the-art solutions of purely visual image matching include: similarity , aﬃne [3,4,5,6], projective [7,8], epipolar  or non-linear  transformations. Nevertheless, there are very few solutions reported on image fragment matching. To the best of our knowledge, there is only one non-semantic, local approach named pattern entropy , based on similarity transformations. Other solutions that can be mentioned include  (the concept of key-places) and .
Near-duplicates matched using the topological approach (Harris-Aﬃne detector and SIFT descriptor applied) randomly selected 1000 distracting image pairs (without similar objects). The database and the method are made publicly available2 . e. the entropy-based approach . 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.
Journal of Electronic Imaging 11, 206–223 (2002) 8. : A visual model weighted cosine transform for image compression and quality assessment. IEEE Transactions on Communications 33(6), 551–557 (1985) 9. : Image quality measures and their performance. IEEE Transactions on Communications 43(12), 2959–2965 (1995) 10. : Statistical analysis of image quality measures. In: European Signal Processing Conf. EUSIPCO 2000, Tampere, Finland, pp. 2181–2184 (2000) 11. : Objective image quality measures derived from digital image power spectra.
Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010, Sydney, Australia, December 13-16, 2010, Proceedings, Part II by Prarthana Shrestha, Hans Weda, Mauro Barbieri, Peter H. N. de With (auth.), Jacques Blanc-Talon, Don Bone, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
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