This paper attempts to introduce a velocity-separation difference model that modifies the previous models in the literature. The improvement of this new model over the previous ones lies in that it performs more reali...
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This paper attempts to introduce a velocity-separation difference model that modifies the previous models in the literature. The improvement of this new model over the previous ones lies in that it performs more realistically than others in the dynamical evolution of congestion. Furthermore, the proposed model is investigated with analytic and numerical method, with the finding that this model can demonstrate some complex physical features observed in real traffic such as the existence of three phases: free flow, coexisting flow, and jam flow; sudden flow drop; traffic hysteresis in transition between the free and the coexisting flow
In this paper, we propose a novel classification algorithm, called geometrical probability covering (GPC) algorithm, to improve classification ability. On the basis of geometrical properties of data, the proposed algo...
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In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, b...
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ISBN:
(纸本)0769525210
In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. The approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably
Radial basis function (RBF) neural network can be used as a universal approximator. In this paper, we propose a novel method to apply RBF net to reconstruct 2-dimensional computerized tomography (CT) images from a sma...
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ISBN:
(纸本)1424406048
Radial basis function (RBF) neural network can be used as a universal approximator. In this paper, we propose a novel method to apply RBF net to reconstruct 2-dimensional computerized tomography (CT) images from a small amount of projection data. In the method, the cross-sectional image is represented by a RBF network, the unknown cross-sectional image vector is replaced by the function of the network's weight vector. As proved by us, the line integral of the weight matrix can be calculated providing the projections of the CT image are known. The ART method can be employed to obtain the final reconstructed CT image. Experiments show that the proposed method can obtain the better reconstructed image than the filtered back projection (FBP), and it is also more efficient than ART method alone
In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with spec...
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In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with special navigational aids. These features are sparse in our application domain and are frequently occluded by other robots. This makes simultaneous acquisition of two or more landmarks difficult. Therefore, we propose a system that requires a single landmark feature. The algorithm is based on range measurement of a single landmark from two arbitrary points whose displacement can be measured using dead-reckoning sensors. Range estimation is done with a stereo vision system. Simulation results show that the robot can localize itself if it can estimates range of the same landmark from two different position and if the displacement between the two position is known.
A novel Parallel-Based Lifting Algorithm (PBLA) for Discrete Wavelet Transform (DWT), exploiting the parallelism of arithmetic operations in all lifting steps, is proposed in this paper. It leads to reduce the cri...
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A novel Parallel-Based Lifting Algorithm (PBLA) for Discrete Wavelet Transform (DWT), exploiting the parallelism of arithmetic operations in all lifting steps, is proposed in this paper. It leads to reduce the critical path latency of computation, and to reduce the complexity of hardware implementation as well. The detailed derivation on the proposed algorithm, as well as the resulting Very Large Scale Integration (VLSI) architecture, is introduced, taking the 9/7 DWT as an example but without loss of generality. In comparison with the Conventional Lifting Algorithm Based Implementation (CLABI), the critical path latency of the proposed architecture is reduced by more than half from (4Tm + 8Ta)to Tm + 4Ta, and is competitive to that of Convolution-Based Implementation (CBI), but the new implementation will save significantly in hardware. The experimental results demonstrate that the proposed architecture has good performance in both increasing working frequency and reducing area.
This paper will discuss a method for presenting a surveillance image captured by an active camera such as one that actively tracks a moving subject as an image that is easily understood by an observer. Active camera s...
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The scope of this paper is the challenging task of classifying terrestrial images of buildings, automatically. Straight line segments and their connectivity incorporate significant information about object shapes. Man...
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This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. Thi...
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Scale is a major concept in many sciences concerned with human activities and physical processes occurring in the world, and directly related to many investigations of spatial objects, including the procedure of spati...
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Scale is a major concept in many sciences concerned with human activities and physical processes occurring in the world, and directly related to many investigations of spatial objects, including the procedure of spatial data mining. In this paper, we attempt to apply the spatial data mining to the field of coal mining, and the technical notion is to generate patterns or rules by means of different scale databases that depict the same subject. The whole research procedure gives readers an understanding of how processes operate at different scales and how they can be linked across scales. At the same time, our study actually presents a new method of image mining as well.
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