Document images belong to a unique class of images where the information is embedded in the language represented by a series of symbols on the page rather than in the visual objects themselves. Since these symbols ten...
Document images belong to a unique class of images where the information is embedded in the language represented by a series of symbols on the page rather than in the visual objects themselves. Since these symbols tend to appear repeatedly, a domain-specific image coding strategy can be designed to facilitate enhanced compression and retrieval. In this paper we describe a coding methodology that not only exploits component-level redundancy to reduce code length but also supports efficient data access. The approach identifies and organizes symbol patterns which appear repeatedly. Similar components are represented by a single prototype stored in a library and the location of each component instance is coded along with the residual between it and its prototype. A representation is built which provides a natural information index allowing access to individual components. Compression results are competitive and compressed-domain access is superior to competing methods. Applications to network-related problems have been considered, and show promising results.
The conditions under which the aggregation of information from interacting agents results in a stable or an unstable collective outcome is an important puzzle in the study of complex systems. We show that if a complex...
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The conditions under which the aggregation of information from interacting agents results in a stable or an unstable collective outcome is an important puzzle in the study of complex systems. We show that if a complex system of aggregated choice respects a mutual knowledge structure, then the prospects of a stable collective outcome are considerably improved. Our domain-independent results apply to collective choice ranging from perception, where an interpretation of sense data is made by a collection of perceptual modules, to social choice, where a group decision is made from a set of preferences held by individuals.
Image processing techniques have already been widely used in various medical applications for decades. With the development of computer and image processing techniques, more and more medical diagnostic systems have be...
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With the development of computer and image processing techniques, the image processing techniques have been widely used in many of the medical applications for decades. Many of these applications are in the fields of ...
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As range images, obtained by active LAser raDAR (LADAR), contain the 3D information necessary for 3D environment understanding, great attention has been attracted, in the field of computervision, to the processing of...
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Most approaches to simultaneously recovering both model parameters and segmentation have relied on an edge field to represent segmentation. This restriction, and the implementations it leads to, have fundamental limit...
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Most approaches to simultaneously recovering both model parameters and segmentation have relied on an edge field to represent segmentation. This restriction, and the implementations it leads to, have fundamental limitations in representing occluded stimuli. The authors develop a framework that overcomes these limitations by using multiple layers of explicit support to represent segmentation. Results from an initial implementation demonstrate that this method can segment images containing occluded objects.< >
My name is Demetri Terzopoulos and my co-chair, John Platt, and I would like to welcome you to the panel on Physically-BasedModeling - Past, Present and Future. I'll start by introducing thepanelists;the affiliati...
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ISBN:
(纸本)0897913531
My name is Demetri Terzopoulos and my co-chair, John Platt, and I would like to welcome you to the panel on Physically-BasedModeling - Past, Present and Future. I'll start by introducing thepanelists;the affiliations you see listed on the screen aresomewhat out of date. I'm Program Leader of modeling and simulation at the Schlumberger lab.ratory for computer Science in Austin, Texas, and I was formerly at Schlumberger Palo Alto Research. I'll speak on the subject of deformable models. John Platt, formerly of Cal Tech, is now Principal Scientist at Synaptics in San Jose, California. He will be concentrating onconstraints and control. Alan Barr is Assistant Professor of computer science at CalTech. Last year he received the computer graphics achievementaward. He'll speak about teleological modeling. David Zeltzer is Associate Professor of computer graphics at the MIT medialab.ratory. He will be speaking on interactive microworlds. Andrew Witkin, formerly of Schlumberger Palo Alto Research, isnow Associate Professor of computer science at Carnegie Mellon University. He will speak about interactive dynamics. Last but not least, we have with us James Blinn, who of courseneeds no introduction. Formerly of JPL, he is now AssociateDirector of the Mathematics Project at Cal Tech. He says he'll haveseveral random comments to make against physically-basedmodeling. I was also asked by the SIGGRAPH organizers to remind theaudience that audio and video tape recording of this panel is notpermitted. Many of you are already familiar with physically-based modeling, so I will attempt only a very simple introduction to this, in myopinion, very exciting paradigm. Physically-based techniquesfacilitate the creation of models capable of automaticallysynthesizing complex shapes and realistic motions that were, untilrecently, attainable only by skilled animators, if at all. Physically-based modeling adds new levels of representation tographics objects. In addition to geometry - forces, torq
In this paper, we present a recognition method which is developed for recognizing shape distorted and partially overlapped flat objects. Several features which are invariant or insensitive to the shape distortions cau...
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In this paper, we present a recognition method which is developed for recognizing shape distorted and partially overlapped flat objects. Several features which are invariant or insensitive to the shape distortions caused by position, scalling and 3-D rotation are proposed. A hierarchical description and Batching technique of the features make the recognition method powerful. The results of a series of experiments demonstrated that the method can be used in robot vision system.
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