This article introduces a new theoretical framework to describe the behavior of the Steinbuch's Lernmatrix. The properties of this old associative memory can be modeled using set theory and order relationships, an...
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ISBN:
(纸本)0819459216
This article introduces a new theoretical framework to describe the behavior of the Steinbuch's Lernmatrix. The properties of this old associative memory can be modeled using set theory and order relationships, analogously to morphological associative memories. The obtained results allow the Lernmatrix, four decades before its creation, to be a good alternative for pattern classification and recognition.
This paper presented a novel algorithm to extract eye features, including pupil center and radius, eye corners and eyelid contours, from frontal face images. Such features are very useful cues for applications like fa...
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This paper presented a novel algorithm to extract eye features, including pupil center and radius, eye corners and eyelid contours, from frontal face images. Such features are very useful cues for applications like face recognition, facial expression recognition and 3D face modeling from 2D images. The novel method is based on color information, Gabor features and the mutual localization relationship between different features. It works in three steps: (1) Pupil center is detected and estimated in H channel of HSV color space, and then pupil radius is estimated and refined;(2) Eye corners are localized using eye-corner filter based on Gabor feature space;(3) Based on the first and second steps, eyelid curves are fitted by spline function. The experimental results on SJTU dataset show sufficient accuracy and robustness of the novel method.
A novel diversity-sampling based Gaussian kernel density estimation (KDE) model was proposed for the representation of multimodal background. Choosing those samples that have diversiform gray-levels in training sequen...
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A novel diversity-sampling based Gaussian kernel density estimation (KDE) model was proposed for the representation of multimodal background. Choosing those samples that have diversiform gray-levels in training sequence, a nonparametric model was built for modeling the scene background. According to the related gray-level, the different weights are given to the different samples in kernel density estimation. This avoids the repetition computation using the total samples, and makes KDE very effective. The experimental results show the good detection performance in the traffic surveillance system.
A simple but effective algorithm which is based on minimizing the maximum discrepancy clustering was presented. Two new metrics of distance between any two triangles is developed. By the new distance metrics, the clus...
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A simple but effective algorithm which is based on minimizing the maximum discrepancy clustering was presented. Two new metrics of distance between any two triangles is developed. By the new distance metrics, the clustering method is easily extended to divide the input mesh into several connected regions. Furthermore, a post-processing algorithm, constrained boundary straightening, was proposed to regularize the shapes of partitioned regions. The experiments show that this two-step solution for mesh segmentation performs well in both region planarity and region shape.
In this paper we construct a novel human body model using convolution surface with articulated kinematic skeleton. The human body's pose and shape in a monocular image can be estimated from convolution curve throu...
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A remote quick rendering model was put forward, based on both the remote mutual control mode of client-server and 3D-texture mapping volume rendering algorithm, aiming at the procession of some medical images of large...
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A remote quick rendering model was put forward, based on both the remote mutual control mode of client-server and 3D-texture mapping volume rendering algorithm, aiming at the procession of some medical images of large data sets. The experiment proves the validity of the rendering model in meeting the demand of rapid and interactive process of medical images on Internet. Compared to the traditional single-computer hardware setting, this model guarantees higher speed and qualified image quality as well.
The algorithm converts the images into basic graph and super graph, and then treats the interferential curve as principal curve to detect principal curve in images. In the detection, an improved shortest path algorith...
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The algorithm converts the images into basic graph and super graph, and then treats the interferential curve as principal curve to detect principal curve in images. In the detection, an improved shortest path algorithm and orientation offset algorithm are used, and finally, the detected curve is removed from the original image. The experiments conducted with a variety of text images show that this algorithm is effective for eliminating interferential curve of text in images.
An approach based on stroke orientation and asymmetric distribution model about feature parameter was proposed, which incorporates structural feature into statistical strategy. An improvement to the algorithm for extr...
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An approach based on stroke orientation and asymmetric distribution model about feature parameter was proposed, which incorporates structural feature into statistical strategy. An improvement to the algorithm for extracting fork points from skeleton images defends the reliability of stroke extraction. The feature vector for statistical recognition is extracted directly from stroke structure, and the asymmetric distribution model is applied to compute distances. The experimental results indicate that the proposed system is effective to handwritten Chinese character recognition.
The purpose of trace reconstruction is to recover information about handwriting sequence from static images of characters, which helps incorporate online methods into offline applications and unify the recognition str...
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The purpose of trace reconstruction is to recover information about handwriting sequence from static images of characters, which helps incorporate online methods into offline applications and unify the recognition strategies of single character and character sequence. A stroke segment-based algorithm was proposed, which is equal to the problem of ordering the stroke segments in nature. Structural graph of stroke segments is extracted from skeleton images, by which the relational graph is created. Trace reconstruction is realized as a globally optimal problem, and the handwriting trace is considered as the path with the totally minimal orientation variance, which can be resolved by searching a Hamiltonian path with minimal cost. The cases of trace reconstruction were analyzed, and the accuracy reaches 93.5% on 200 images. The experimental results indicate the proposed approach is effective to the reconstruction of handwriting traces of handwritten numerals.
This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the...
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This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the models to the interest region. In training stage, according to the manual labeled feature points, the relative AAM is constructed and the corresponding average feature is obtained. In recognition stage, the interesting hand gesture region is firstly segmented by skin and movement ***, the models are fitted to the image that includes the hand gesture, and the relative features are ***, the classification is done by comparing the extracted features and average features. 30 different gestures of Chinese sign language are applied for testing the effectiveness of the method. The Experimental results are given indicating good performance of the algorithm.
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