this paper introduces a novel approach for dynamic structuring of contextual lattices. It is anticipated that the approach can be applied to improve the accuracy of word-segmentation patterns in autonomous text recogn...
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the historical documents are valuable cultural heritages and sources for the study of history, social aspect and life at that time. the digitalization of historical documents aims to provide instant access to the arch...
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In this paper, we adapt the idea of Intelligent Scissors for contour tracking in dynamic image sequence. Tracking contour of human can therefore be converted to tracking seed points in images by making use of the prop...
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ISBN:
(纸本)0769521223
In this paper, we adapt the idea of Intelligent Scissors for contour tracking in dynamic image sequence. Tracking contour of human can therefore be converted to tracking seed points in images by making use of the properties of the optimal path (Intelligent Edge). the main advantage of the approach is that it can handle correctly occlusions that occur frequently when human is moving. Non-Uniform Rational B-Spline (NURBS) are used to represent parametrically the contour that we want to track In order to track robustly the contour in images, similarity and compatibility measurements of the edge are computed as the weighting functions of optimal estimator To reduce dramatically the computational load, an efficient method for extracting the region that we are interested in is proposed. Experiments show that our approach works robustly with sequences with frequent occlusions.
this paper presents a feature recognition (FR) technique that separates protrusions bounded by freeform surface geometry. the method can also generate complementary male/female assembly features at the interface betwe...
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ISBN:
(纸本)0769520758
this paper presents a feature recognition (FR) technique that separates protrusions bounded by freeform surface geometry. the method can also generate complementary male/female assembly features at the interface between components. A novel heuristic that uses edge curvature continuity is applied to direct the search and the construction of protrusion boundaries. the result is represented as a cellular model. the objective is to manufacture complex prototype assemblies on multi-axis machining centres. After describing the algorithm and presenting some examples of its application the paper concludes by discussing the approaches limitations.
In this paper, we present a new method to obtain the contours of color faces. First, we introduce a new nonlinear skin classifier to detect the human skin information in images. then, a split machine (SM) places an ad...
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ISBN:
(纸本)0769521223
In this paper, we present a new method to obtain the contours of color faces. First, we introduce a new nonlinear skin classifier to detect the human skin information in images. then, a split machine (SM) places an adaptive grid over an image according to the low-level information detected in the representative regions. By filtering the redundant points extracted from the actively divided grid, we obtain a set of points that can coarsely construct the contour of the detailed skin region. Finally, we refine the contour by computing the local minimum energy of each point. Experimental results show that our proposed approach is capable of constructing the contours of color faces.
the major challenges that sign language recognition (SLR) now faces are developing methods that solve large vocabulary continuous sign problems. In this paper, large vocabulary continuous SLR based on transition movem...
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ISBN:
(纸本)0769521223
the major challenges that sign language recognition (SLR) now faces are developing methods that solve large vocabulary continuous sign problems. In this paper, large vocabulary continuous SLR based on transition movement models is proposed. the proposed method employs the temporal clustering algorithm to cluster a large amount of transition movements, and then the corresponding training algorithm is also presented for automatically segmenting and training these transition movement models. the clustered models can improve the generalization of transition movement models, and are very suitable for large vocabulary continuous SLR. At last, the estimated transition movement models, together with sign models, are viewed as candidate models of the Viterbi search algorithm for recognizing continuous sign language. Experiments show that continuous SLR based on transition movement models has good performance over a large vocabulary of 5113 signs.
Clustering is crucial to many applications in patternrecognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most suffer from several shortcomings. We fo...
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ISBN:
(纸本)3540223436
Clustering is crucial to many applications in patternrecognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most suffer from several shortcomings. We formulate requirements for efficient encoding, resistance to noise, and ability to discover the number of clusters automatically.
this paper presents an HMM based hierarchical clustering method, aiming at the extraction of typical temporal sequences, and outliers are discarded in the process of clustering. After the Baum-Welch training step of H...
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ISBN:
(纸本)0769521223
this paper presents an HMM based hierarchical clustering method, aiming at the extraction of typical temporal sequences, and outliers are discarded in the process of clustering. After the Baum-Welch training step of HMM, TWM (Transition Weighted Matrix) is used as the features of sample sequences, thus the original clustering problem is converted to a relatively easy problem of points clustering in a high dimensional space. By using hierarchical clustering and NCut (Normalized Cut) method, the unsteadiness in separation is efficiently prevented and the time consuming is relatively small. the method is used in unsupervised learning of typical hand gestures and facial expressions.
Spiking neural networks represent a more plausible model of real biological neurons where time is considered as an important feature for information representation and processing in the human brain. In this paper, we ...
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ISBN:
(纸本)9812388737
Spiking neural networks represent a more plausible model of real biological neurons where time is considered as an important feature for information representation and processing in the human brain. In this paper, we apply spiking neural networks with dynamic synapses for patternrecognition in multidimensional data. the neurons are based on the integrate and-fire model, and are connected using a biologically plausible model of dynamic synapses. Unlike the conventional synapse employed in artificial neural networks, which is considered as a static entity with a fixed weight, the dynamic synapse (weightless synapse) efficacy changes upon the arrival of input spikes, and depends on the temporal structure of the impinging spike train. the training of the free parameters of the spiking network is performed using an evolutionary strategy (ES) where real values are used to encode the dynamic synapse parameters, which underlie the learning process.. the results show that spiking neurons with dynamic synapses are capable of patternrecognition by means of spatio-temporal encoding.
this paper presents a face detection method based on Kernel Fisher Discriminant analysis (KFD). Kernel based methods have been extensively investigated both in theories and applications, such as SVM and Kernel PCA. Us...
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ISBN:
(纸本)0769521223
this paper presents a face detection method based on Kernel Fisher Discriminant analysis (KFD). Kernel based methods have been extensively investigated both in theories and applications, such as SVM and Kernel PCA. Using the kernel trick, Linear Fisher Discriminant can be extended to non-linear case. Since the distribution of face patterns is very complex and highly nonlinear, using nonlinear classification tools can hopefully tackle the problem of face detection. We explore the application of KFD in the task of frontal face detection. the experimental results prove the effectiveness of KFD in the face detection problem.
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