In this paper we present a comparative analysis of two algorithms for image representation with application to recognition of 3D face scans withthe presence of facial expressions. We begin with processing of the inpu...
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In this paper we present a comparative analysis of two algorithms for image representation with application to recognition of 3D face scans withthe presence of facial expressions. We begin with processing of the input point cloud based on curvature analysis and range image representation to achieve a unique representation of the face features. then, subspace projection using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are performed. Finally classification with different classifiers will be performed.
this paper presents a quantitative and qualitative analysis of surface representations used in recent statistical models of human shape and pose. Our analysis and comparison framework is twofold. Firstly, we qualitati...
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ISBN:
(纸本)9783642315671
this paper presents a quantitative and qualitative analysis of surface representations used in recent statistical models of human shape and pose. Our analysis and comparison framework is twofold. Firstly, we qualitatively examine generated shapes and poses by interpolating points in the shape and pose variation spaces. Secondly, we evaluate the performance of the statistical human models in the context of human shape and pose reconstruction from silhouette. the analysis demonstrates that body shape variation can be controlled with a lower dimensional model using a PCA basis in the Euclidean space. In addition, the Euclidean representation is shown to give more accurate shape estimates than other surface representations in the absence of pose variation. Furthermore, the analysis indicates that shape and pose parametrizations based on translation and rotation invariant representations are not robust for reconstruction from silhouette without pose initialization.
the proceedings contain 37 papers. the topics discussed include: matching hierarchies of deformable shapes;edition within a graph kernel framework for shape recognition;coarse-to-fine matching of shapes using disconne...
ISBN:
(纸本)3642021239
the proceedings contain 37 papers. the topics discussed include: matching hierarchies of deformable shapes;edition within a graph kernel framework for shape recognition;coarse-to-fine matching of shapes using disconnected skeletons by learning class-Specific boundary deformations;an optimization-based approach to mesh smoothing: reformulation and extensions;graph-based analysis of nasopharyngeal carcinoma with Bayesian network learning methods;computing and visualizing a graph-based decomposition for non-manifold shapes;graph-based registration of partial images of city maps using geometric hashing;a polynomial algorithm for submap isomorphism: application to searching patterns in images;a recursive embedding approach to median graph computation;and inexact matching of large and sparse graphs using Laplacian eigenvectors.
the proceedings contain 28 papers. the topics discussed include: user identification and object recognition in clutter scenes based on RGB-depth analysis;spatial measures between human poses for classification and und...
ISBN:
(纸本)9783642315664
the proceedings contain 28 papers. the topics discussed include: user identification and object recognition in clutter scenes based on RGB-depth analysis;spatial measures between human poses for classification and understanding;real-time pose estimation using constrained dynamics;an NVC emotional model for conversational virtual humans in a 3D chatting environment;an event-based architecture to manage virtual human non-verbal communication in 3D chatting environment;improving gestural communication in virtual characters;multi-view body tracking with a detector-driven hierarchical particle filter;real-time multi-view human motion tracking using particle swarm optimization with resampling;a comparative study of surface representations used in statistical human models;combining skeletal pose with local motion for human activity recognition;and a new marker-less 3D kinect-based system for facial anthropometric measurements.
In the field of structural patternrecognitiongraphs constitute a very common and powerful way of representing objects. the main drawback of graphrepresentations is that the computation of various graph similarity m...
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ISBN:
(纸本)9783642208447
In the field of structural patternrecognitiongraphs constitute a very common and powerful way of representing objects. the main drawback of graphrepresentations is that the computation of various graph similarity measures is exponential in the number of involved nodes. Hence, such computations are feasible for rather small graphs only. One of the most flexible graph similarity measures is graph edit distance. In this paper we propose a novel approach for the efficient computation of graph edit distance based on bipartite graph matching by means of the Volgenant-Jonker assignment algorithm. Our proposed algorithm provides only suboptimal edit distances, but runs in polynomial time. the reason for its sub-optimality is that edge information is taken into account only in a limited fashion during the process of finding the optimal node assignment between two graphs. In experiments on diverse graphrepresentations we demonstrate a high speed up of our proposed method over a traditional algorithm for graph edit distance computation and over two other sub-optimal approaches that use the Hungarian and Munkres algorithm. Also, we show that classification accuracy remains nearly unaffected by the suboptimal nature of the algorithm.
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from diff...
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ISBN:
(纸本)9783642208447
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. based on these operations the users can produce a final image segmentation that best suits their applications. this work can be used for applications where we need accuracy in image segmentation, in annotating images or creating ground truth among others.
In the barrel region at the Belle II detector, a time-of-propagation (TOP) counter is foreseen for particle identification. In this counter the particle identity is determined from a complicated pattern in the time an...
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In the barrel region at the Belle II detector, a time-of-propagation (TOP) counter is foreseen for particle identification. In this counter the particle identity is determined from a complicated pattern in the time and the position of Cherenkov photon hits. We present an extended likelihood method for particle identification, which is based on an analytical construction of the likelihood function. (C) 2010 Elsevier B.V. All rights reserved.
A new patternrecognition algorithm applied for determination of rings in two-dimensional spectra from RICH detectors is presented. the method is based on Gold's deconvolution algorithm. It enables one to concentr...
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A new patternrecognition algorithm applied for determination of rings in two-dimensional spectra from RICH detectors is presented. the method is based on Gold's deconvolution algorithm. It enables one to concentrate the contents of one ring into a point located at its center. the algorithm is capable of identifying curves of any shape, even of an irregular one. (C) 2010 Elsevier B.V. All rights reserved.
this paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. these graphs constitutes an ingredient of Size theory, a geometrical/topological ap...
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ISBN:
(纸本)9783642208447
this paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. these graphs constitutes an ingredient of Size theory, a geometrical/topological approach to shape analysis and comparison. A global method for reducing size graphs is presented, together with a theorem stating that size graphs reduced in such a way preserve all the information in terms of multidimensional size functions. this approach can lead to simplify the effective computation of discrete multidimensional size functions, as shown by examples.
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