the proceedings contain 36 papers from the graph-basedrepresentations in patternrecognition - 5th IAPR internationalworkshop, GbRPR 2005, Proceedings. the topics discussed include: vectorized image segmentation via...
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the proceedings contain 36 papers from the graph-basedrepresentations in patternrecognition - 5th IAPR internationalworkshop, GbRPR 2005, Proceedings. the topics discussed include: vectorized image segmentation via trixel agglomeration;graph transformation in document image analysis: approaches and challenges;a vascular network growth estimation algorithm using random graphs;a linear generative model for graph structure;comparing string representations and distances in a natural images classification task;and reduction strings: a representation of symbolic hierarchical graphs suitable for learning.
Segmentation algorithms based on an energy minimisation framework often depend on a scale parameter which balances a fit to data and a regularising term. Irregular pyramids are defined as a stack of graphs successivel...
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ISBN:
(纸本)9783540729020
Segmentation algorithms based on an energy minimisation framework often depend on a scale parameter which balances a fit to data and a regularising term. Irregular pyramids are defined as a stack of graphs successively reduced. Within this framework, the scale is often defined implicitly as the height in the pyramid. However, each level of an irregular pyramid can not usually be readily associated to the global optimum of an energy or a global criterion on the base level graph. this last drawback is addressed by the scale set framework designed by Guigues. the methods designed by this author allow to build a hierarchy and to design cuts within this hierarchy which globally minimise an energy. this paper studies the influence of the construction scheme of the initial hierarchy on the resulting optimal cuts. We propose one sequential and one parallel method with two variations within both. Our sequential methods provide partitions near an energy lower bound defined in this paper. Parallel methods require less execution times than the sequential method of Guigues even on sequential machines.
this paper describes a PDA-based MMCR (MultiModal Command Recognizer for PDA control and handling) using double-touching with a finger by coupling embedded speech and KSSL recognize;and suggests an improved synchroniz...
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ISBN:
(纸本)9780769528670
this paper describes a PDA-based MMCR (MultiModal Command Recognizer for PDA control and handling) using double-touching with a finger by coupling embedded speech and KSSL recognize;and suggests an improved synchronization method between multi-modalities for simultaneous multi-modality, for a patternrecognition-based neo multi-modal HCI. the MMCR fuses and recognizes 16 word-based command models that are represented by stylus, speech and KSSL (Korean Standard Sign Language), and then translates the recognition result into synthetic speech and visual illustration, for multi-modal PDA handling and interaction.
We introduce a method for computing homology groups and their generators of a 2D image, using a hierarchical structure i.e. irregular graph pyramid. Starting from an image, a hierarchy of the image is built, by two op...
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ISBN:
(纸本)9783540729020
We introduce a method for computing homology groups and their generators of a 2D image, using a hierarchical structure i.e. irregular graph pyramid. Starting from an image, a hierarchy of the image is built, by two operations that preserve homology of each region. Instead of computing homology generators in the base where the number of entities (cells) is large, we first reduce the number of cells by a graph pyramid. then homology generators are computed efficiently on the top level of the pyramid, since the number of cells is small, and a top down process is then used to deduce homology generators in any level of the pyramid, including the base level i.e. the initial image. We show that the new method produces valid homology generators and present some experimental results.
the traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of cities, the problem is approximated int...
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ISBN:
(纸本)9783540729020
the traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of cities, the problem is approximated into a simpler form containing smaller number of cities, which is then solved optimally. graph pyramid solution strategies, in a bottom-up manner using Boruvka's minimum spanning tree, convert a 2D Euclidean TSP problem with a large number of cities into successively smaller problems (graphs) with similar layout and solution, until the number of cities is small enough to seek the optimal solution. Expanding this tour solution in a top-down manner to the lower levels of the pyramid approximates the solution. the new model has an adaptive spatial structure and it simulates visual acuity and visual attention. the model solves the TSP problem sequentially, by moving attention from city to city withthe same quality as humans. graph pyramid data structures and processing strategies are a plausible model for finding near-optimal solutions for computationally hard patternrecognition problems.
We compare different statistical characterizations of a set of strings, for three different histogram-based distances. Given a distance, a set of strings may be characterized by its generalized median, i.e., the strin...
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ISBN:
(纸本)9783540729020
We compare different statistical characterizations of a set of strings, for three different histogram-based distances. Given a distance, a set of strings may be characterized by its generalized median, i.e., the string -over the set of all possible strings- that minimizes the sum of distances to every string of the set, or by its set median, i.e., the string of the set that minimizes the sum of distances to every other string of the set. For the first two histogram-based distances, we show that the generalized median string can be computed efficiently;for the third one, which biased histograms with individual substitution costs, we conjecture that this is a NP-hard problem, and we introduce two different heuristic algorithms for approximating it. We experimentally compare the relevance of the three histogram-based distances, and the different statistical characterizations of sets of strings, for classifying images that are represented by strings.
At present, mobile computation is developing rapidly for location-based services. For the online GIS or cartography of moving objects, the techniques of progressively refined details greatly reduce the overhead of sto...
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ISBN:
(纸本)9780819469502
At present, mobile computation is developing rapidly for location-based services. For the online GIS or cartography of moving objects, the techniques of progressively refined details greatly reduce the overhead of storage, computation, display, and communication resources. Again, human cognition about the reality is made at multi-scales of abstraction. Multi-scale representations of the moving object trajectory are required upon human hierarchical cognition and progressively refined details modeling. To this end, wavelet-based multi-scale representations of the motion trajectory are presented in this paper. We consider parametric motion and a sequence of spatio-temporal coordinates as database representations of the motion trajectory. Correspondingly, multi-scale wavelets representations are considered as computing representations of the motion trajectory. the wavelet transform is applied to time-series of spatial coordinates for finding dramatic or gradual changes of motion speed at each scale. Multi-scale wavelets representations of the motion trajectory have revealed global motion trends at the large scale and local motion details at the small scale. Inherently, spatio-temporal coordinates, motion, and dynamics are three-scale representations of spatio-temporal semantics. Multi-scale representations of motion trajectory are experimentally illustrated. Our work is devoted not only to mobile computation but also to extension of wavelet analysis into geometry data processing.
graph pyramids are often used for representing irregular image pyramids. For the 2D case, combinatorial pyramids have been recently defined in order to explicitly represent more topological information than graph pyra...
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graph pyramids are often used for representing irregular image pyramids. For the 2D case, combinatorial pyramids have been recently defined in order to explicitly represent more topological information than graph pyramids. the main contribution of this work is the definition of pyramids of n-dimensional (nD) generalized maps. this extends the previous works to any dimension, and generalizes them in order to represent any type of pyramid constructed by using any removal and/or contraction operations. We give basic algorithms that allow to build an nD generalized pyramid that describes a multi-level segmented image. A pyramid of nD generalized maps can be implemented in several ways. We propose three possible representations and give conversion algorithms. (c) 2005patternrecognition Society. Published by Elsevier Ltd. All rights reserved.
Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Such pyramids are used within the segmentation framework to encode a hierarchy of partitions. the different graph models use...
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Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Such pyramids are used within the segmentation framework to encode a hierarchy of partitions. the different graph models used within the irregular pyramid framework encode different types of relationships between regions. this paper compares different graph models used within the irregular pyramid framework according to a set of relationships between regions. We also define a new algorithm based on a pyramid of combinatorial maps which allows to determine if one region contains the other using only local calculus. (c) 2005patternrecognition Society. Published by Elsevier Ltd. All rights reserved.
Algorithms for the analysis of graph sequences are proposed in this paper. In particular, we study the problem of recovering missing information and predicting the Occurrence of nodes and edges in time series of graph...
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Algorithms for the analysis of graph sequences are proposed in this paper. In particular, we study the problem of recovering missing information and predicting the Occurrence of nodes and edges in time series of graphs. Two different recovery schemes are developed. the first scheme uses reference patterns that are extracted from a training set of graph sequences, while the second method is based on decision tree induction. Our work is motivated by applications in Computer network analysis. However, the proposed recovery and prediction schemes are generic and can be applied in other domains as well. (c) 2005patternrecognition Society. Published by Elsevier Ltd. All rights reserved.
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