This paper presents a method of camera self-calibration based on structural information of scenes containing isosceles ***,we establish the homography between a plane in the scene and that of an image and provide the ...
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This paper presents a method of camera self-calibration based on structural information of scenes containing isosceles ***,we establish the homography between a plane in the scene and that of an image and provide the expression of the absolute conic in space under an affine coordinates *** using the homography and the constraints of circular points on camera intrinsic parameters,we construct a group of nonlinear equations and determine the camera intrinsic parameters by Levenberg-Marquardt *** experimental results of both synthetic data and real-world data show that our method possesses a high accuracy.
Knowledge engineering stems from E. A. Figenbaum＇s proposal in 1977, but it will enter a new decade with the new challenges. This paper first summarizes three knowledge engineering experiments we have undertaken to s...
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Knowledge engineering stems from E. A. Figenbaum＇s proposal in 1977, but it will enter a new decade with the new challenges. This paper first summarizes three knowledge engineering experiments we have undertaken to show possibility of separating knowledge development from intelligent software development. We call it the ICAX mode of intelligent application software generation. The key of this mode is to generate knowledge base, which is the source of intelligence of ICAX software, independently and parallel to intelligent software development. That gives birth to a new and more general concept ＂knowware＂. Knowware is a commercialized knowledge module with documentation and intellectual property, which is computer operable, but free of any built-in control mechanism, meeting some industrial standards and embeddable in software/hardware. The process of development, application and management of knowware is called knowware engineering. Two different knowware life cycle models are discussed： the furnace model and the crystallization model. Knowledge middleware is a class of software functioning in all aspects of knowware life cycle models. Finally, this paper also presents some examples of building knowware in the domain of information system engineering.
We propose an appearance-based image clustering approach called GGCI (global geometric clustering for image). For face images taken with varying pose, expression, eyes (wearing sunglasses or not) or object images unde...
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A novel graph seriation method based random graph theory is proposed in this paper. By seriation processing, graphs can be converted to string through constructing toroidal catch digraph. Seriated graph distance is us...
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A novel graph seriation method based random graph theory is proposed in this paper. By seriation processing, graphs can be converted to string through constructing toroidal catch digraph. Seriated graph distance is using to represent the similarity between graphs. It measures the structural differences between graphs based on the dynamic warping technique. Dynamic time warping distance used in the paper is evaluated by dynamic programming. The results of our experiments demonstrate that the proposed method is eligible for graph distance measure
In this paper, the kurtosis-based method for the classification of mental activities is proposed. The EEG signals were recorded during imagination of left or right hand movement. The kurtosis of EEG and its dynamic pr...
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An ideal knowledge flow network passes right knowledge to the right person at the right time. Trust between knowledge nodes influences the efficiency of knowledge interchange in an organization. This paper presents a ...
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Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content s...
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A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the ...
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We propose two geometric structure based approaches GGCI (global geometric clustering for image) and GSIM (geometric structure based image matching) for image clustering and image matching, respectively. For face imag...
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ISBN:
(纸本)9781424404759
We propose two geometric structure based approaches GGCI (global geometric clustering for image) and GSIM (geometric structure based image matching) for image clustering and image matching, respectively. For face images or object images taken with varying factors, the GGCI approach learns the global geometric structure of images space and clusters images based on geodesic distance instead of Euclidean distance and the extended nearest neighbor approach. The GSIM approach uses the minimal Euclidean distance between parts of image and the pattern and its variations as matching criteria and threshold strategy for image matching. We demonstrate experimentally that the GGCI approach achieves lower error rates and the GSIM approach brings down the sensitivity of gray values to change in radiometry and reduces multi local extrema to some extent.
We present a new distance for the contour-based shapes recognition which we called shape edit distance (SED). Unlike the traditional distance, SED takes into account the spatial deformation of shapes. To compute the s...
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We present a new distance for the contour-based shapes recognition which we called shape edit distance (SED). Unlike the traditional distance, SED takes into account the spatial deformation of shapes. To compute the shape edit distance, we convert shapes to string sequences so that string matching techniques can be used. We pose the problem of string matching as a maximum a posteriori probability (MAP) alignment of the string sequences for shapes and compute the shape edit distance by finding the sequence of string edit operations which minimizes the cost of the path traversing the edit lattice. Experiments demonstrate the utility of the shape edit distance on a number of image retrieval and clustering problems
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