By introducing relative velocities of arbitrary number of cars ahead into the full velocity difference models (FVDM), we present a forward looking relative velocity model (FLRVM) of cooperative driving control system....
By introducing relative velocities of arbitrary number of cars ahead into the full velocity difference models (FVDM), we present a forward looking relative velocity model (FLRVM) of cooperative driving control system. To our knowledge, the model is an improvement over the similar extension in the forward looking optimal velocity models (FLOVM), because it is more reasonable and realistic in implement of incorporating intelligent transportation system in traffic. Then the stability criterion is investigated by the linear stability analysis with finding that new consideration theoretically lead to the improvement of the stability of traffic flow, and the validity of our theoretical analysis is confirmed by direct simulations. In addition, nonlinear analysis of the model shows that the three waves: triangular shock wave, soliton wave and kink-antikink wave appear respectively in stable, metastable and unstable regions. These correspond to the solutions of the Burgers equation, Korteweg-de Vries (KdV) equation and modified Korteweg-de Vries (mKdV) equation.
Precise pupil features detection is an important factor for face recognition. This paper presents a robust and accurate algorithm to precisely estimate pupil features: pupil center and pupil radius. First, a pupil par...
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Precise pupil features detection is an important factor for face recognition. This paper presents a robust and accurate algorithm to precisely estimate pupil features: pupil center and pupil radius. First, a pupil parameters estimation step is taken and a weight ring mask is created. Then, a weighted Hough transform is used to precisely extract pupil features. Because of the estimation step, the influence of eyelid and eyelash is largely eliminated. The experimental results show very good robustness and accuracy
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 real...
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When computer vision technique is used in robotics, robotic hand-eye calibration is a very important research task. Many algorithms have been proposed for hand-eye calibration. Based on these algorithms, we introduce ...
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When computer vision technique is used in robotics, robotic hand-eye calibration is a very important research task. Many algorithms have been proposed for hand-eye calibration. Based on these algorithms, we introduce a new hand-eye calibration algorithm in this paper, which employs the screw motion theory to establish a hand-eye matrix equation by using quaternion and gets a simultaneous result for rotation and translation by solving linear equations. The algorithm proposed in this paper has high and stable computational efficiency without non-linear minimization and can be understood easily. Both simulations and real experiments show the superiority of our algorithm over the comparative algorithms
An efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. First, candidate facial components are efficiently collected by cascaded boosting of Haar...
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ISBN:
(纸本)0769525210
An efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. First, candidate facial components are efficiently collected by cascaded boosting of Haar-like features. The candidates may include false positives and multiple detections. Then, geometrical distribution of facial components is imposed on the candidates to select the optimal configuration. For simplicity, we suppose full dependence between the components and model it with multivariate Gaussian. The effectiveness of the framework is evaluated with experiments
In wireless sensor networks, target classification differs from that in centralized sensing systems because of the distributed detection, wireless communication and limited resources. We study the classification probl...
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In wireless sensor networks, target classification differs from that in centralized sensing systems because of the distributed detection, wireless communication and limited resources. We study the classification problem of moving vehicles in wireless sensor networks using acoustic signals emitted from vehicles. Three algorithms including wavelet decomposition, weighted k-nearest-neighbor and Dempster-Shafer theory are combined in this paper. Finally, we use real world experimental data to validate the classification methods. The result shows that wavelet based feature extraction method can extract stable features from acoustic signals. By fusion with Dempster's rule, the classification performance is improved.
In this paper, we employ the concept of characteristic line to show some useful properties of planar homography matrix. These properties relate the characteristic line of a planar homography matrix with Euler angles o...
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ISBN:
(纸本)0769525210
In this paper, we employ the concept of characteristic line to show some useful properties of planar homography matrix. These properties relate the characteristic line of a planar homography matrix with Euler angles of the planar pattern. Based on the characteristic line, a new method of linear camera calibration is proposed and a strategy to select poses of planar pattern during taking calibration images is suggested. This strategy can help ensure accuracy of calibration. Experiment results including both simulated data and real images validate the method and strategy
Anisotropic diffusion can remove noise to some extent in imageprocessing. However the contradiction between diffusion and preservation still exists. In this paper, a new nonlinear diffusion model for image noise remo...
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Anisotropic diffusion can remove noise to some extent in imageprocessing. However the contradiction between diffusion and preservation still exists. In this paper, a new nonlinear diffusion model for image noise removal and feature preservation is presented. This model treats inhomogeneity region and image feature adaptively by discontinuity measure and local gradient information. A well balance between diffusion and preservation is also made in this new diffusion method. Experiments results show that the proposed method has high performance compared to other literature methods and is an ideal edge-preserving filtering method. In addition, we use block-based noise estimation to estimate deviation in diffusion equation
By introducing the velocity difference between the preceding car and the car before the preceding one into the optimal velocity model (OVM), we present an extended dynamical model which takes into account the next-nea...
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By introducing the velocity difference between the preceding car and the car before the preceding one into the optimal velocity model (OVM), we present an extended dynamical model which takes into account the next-nearest-neighbor interaction. The stability condition of this model is derived by considering a small perturbation around the uniform flow solution with finding that traffic congestion is suppressed efficiently by incorporating the effect of new consideration. Then we investigate the property of the model using numerical methods. The results indicate that the next-nearest-neighbor interaction has important impacts on the coexisting flow, the relation between flow and density, and the propagation speed of small disturbance (PSSD). In addition, we have a try to further enhance the stability of traffic flow by introducing the relative velocity of an arbitrary number of cars in front, but the analysis of linear stability shows it is poor for our purpose
Knowing the locations of nodes in wireless sensor networks (WSN) is essential for many applications. Nodes in a WSN can have multiple capabilities and exploiting one or more of the capabilities can help to solve the l...
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Knowing the locations of nodes in wireless sensor networks (WSN) is essential for many applications. Nodes in a WSN can have multiple capabilities and exploiting one or more of the capabilities can help to solve the localization problem. In this paper, we assume that each node in a WSN has the capability of distance measurement and present a location computation technique called linear intersection for node localization. We also propose an applied localization model using linear intersection and do some concerned experiments to estimate the location computation algorithm.
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