By Sergey V. Sai, Ilya S. Sai, Nikolay Yu. Sorokin (auth.), Jacques Blanc-Talon, Don Bone, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
This quantity collects the papers permitted for presentation on the twelfth Int- nationwide convention on “Advanced strategies for clever imaginative and prescient structures” (ACIVS 2010). Following the ?rst assembly in Baden-Baden (Germany) in 1999, whichwaspartofalargemulticonference,theACIVSconferencethendeveloped into an self sufficient scienti?c occasion and has ever due to the fact that maintained the culture of being a unmarried music convention. ACIVS 2010 attracted laptop scientists from 29 di?erent international locations, usually from Europe, Australia, and the united states, but in addition from Asia. even if ACIVS is a convention on all components of picture and video processing, submissions are inclined to assemble inside definite significant ?elds of curiosity. This 12 months 3D and intensity processing and computing device imaginative and prescient and surveillance have been renowned subject matters. Noteworthy are the starting to be variety of papers relating to theoretical devel- ments. we want to thank the invited audio system Mubarak Shah (University of significant Florida), Richard Kleihorst (VITO, Belgium), Richard Hartley (A- tralian nationwide University), and David Suter (Adelaide collage) for his or her precious contributions.
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Additional resources for Advanced Concepts for Intelligent Vision Systems: 12th International Conference, ACIVS 2010, Sydney, Australia, December 13-16, 2010, Proceedings, Part I
Based on extensive test with numerous images and diﬀerent keypoint detectors, the recommended parameter values are: m = 30 and T = 45%. 5 Topology versus Geometry – The Experimental Veriﬁcation To compare the topological algorithm to its aﬃne counterpart, we have used a database of 100 diversiﬁed images captured under various lighting conditions. Within the ten thousand image pairs, over one thousand pairs contain similar objects. In the experiments, we used these images pairs and, additionally, Table 1.
The constraint is based on the orientation of vectors connecting a given keypoint to its matched neighbors. An illustrative example is given in Fig. 1. Fig. 1. For each pair of matched keypoints, the largest subset of orientation-ordered neighbors is found. An exemplary subset of size 5 is shown. When we order the vectors in the ﬁrst image, a similarly ordered sequence of the corresponding vectors is generally expected in the other image. However, if two keypoints are falsely matched, vectors are usually ordered very diﬀerently.
In the latter case, the quality of images is very poor and matching is far from perfect, but nevertheless still possible. 28 4 ´ A. Sluzek and M. Paradowski Conclusions In the paper we have outlined a topology-based approach to image fragment matching in real time. In earlier papers, , we have suggested applications of the proposed method in assisting visually handicapped people and autonomous agents navigating in unknown and unexplored environments. The presented solution makes such systems feasible.
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.)