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
We propose a novel method, the complete two-dimensional principal component analysis (complete 2DPCA), for image features extraction. Compared to the original 2DPCA, complete 2DPCA not only gain a higher recognition r...
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We propose a novel method, the complete two-dimensional principal component analysis (complete 2DPCA), for image features extraction. Compared to the original 2DPCA, complete 2DPCA not only gain a higher recognition rate, but also reduce the feature coefficients needed for face recognition. Complete 2DPCA is based on 2D image matrices. Two image covariance matrices are constructed directly using the original image matrix and theirs eigenvectors are derived for image feature extraction. Our experiments were performed on ORL face database, and experimental results show that the proposed method has an encouraging performance
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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Classification of multisource remote sensing images has been studied for decades, and many methods have been proposed. Most of these studies focus on how to improve the classifiers in order to obtain higher classifica...
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Classification of multisource remote sensing images has been studied for decades, and many methods have been proposed. Most of these studies focus on how to improve the classifiers in order to obtain higher classification accuracy. However, as we know, even if the most promising neural network method, its good performance not only depends on the classifier itself, but also has relation to the training pattern (i.e. features). On consideration of this aspect, we propose an approach to feature selection and classification of multisource remote sensing image based on residual error in this paper. In particular, a feature-selection scheme approach is proposed, which is to select effective subsets of features as inputs of a classifier by taking into account the residual error associated with each land-cover class. In addition, a classification technique base on selected features by using a feedforward neural network is investigated. The results of experiments carried out on a multisource data set confirm the validity of the proposed approach
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
The performances of a well-known GHR car-following model was investigated byusing numerical simulations in describing the acceleration and deceleration process induced by themotion of a leading car. It is shown that i...
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The performances of a well-known GHR car-following model was investigated byusing numerical simulations in describing the acceleration and deceleration process induced by themotion of a leading car. It is shown that in GHR model vehicle is allowed to run arbitrarily closetogether if their speed are identical, and it waves aside even though the separation is larger thanits desired distance. Based on these investigations, a modified GHR model which features a newnonlinear term which attempts to adjust the inter-vehicle spacing to a certain desired value wasproposed accordingly to overcome these deficiencies. In addition, the analysis of the additivenonlinear term and steady-state flow of the new model were studied to prove its rationality.
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 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
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.
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
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