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In order to improve the accuracy of pedestrian detection, we proposed an algorithm of multi-channel feature detection based on Discrete Cosine Transform (DCT). We use a two-layer convolution network for arranging the image information after DCT to build a new channel in the frequency domain. The channel can describe complex textures about pedestrian. Combined with the features of the histogram of...
This work seeks to improve upon the accuracy of birdsong analysis based species recognition. We intend to accomplish this by creating a more effective bird syllable segmentation algorithms (MIRS), Support Vector machine based classifiers are used to train the features of IRS and MIRS. The experimental results show the effectiveness of the proposed algorithm.
Object detection is a significant step of intelligent video surveillance. The existing methods achieve the goals by technically designing or learning special features and detection models. Conversely, we propose a method to simulate the mechanism of memory and prediction in our brain. Firstly, a fix-sized window is slid on a static image to generate sequences. Then, a convolutional neural network...
Rail track extraction from the image can be used to determine the position of the rails ahead of a train, which is one of the fundamental tasks for vision-based driver support systems in railways. This paper introduces a method that extracts rails by matching the edge features of the real image to the candidate rail patterns which is parameterically modeled, and the geometric constraints of the rail...
Recently, it has been a popular issue that using visual perception for autonomous navigation in Unmanned Aerial Vehicle (UAV). However, in the field of computer vision, the restoration of the three-dimensional shape from the two-dimensional image video stream captured by camera is the central issue, which includes the feature point selection, tracking studies, and structural problems of uncalibrated...
This paper focuses on line features extraction and fusion problems in sensing the environment for indoor mobile robot with sonar sensor. A sonar model is firstly built using a large amount of sonar experimental data that is obtained through testing different ranges for the sonar sensor. Then the sonar data consisted of points detected from the sonar is classified into different line segments using...
Aimed that the image applied in CSF(Cavity Spatial Filter)auto-alignment control of SG-II-UP(Shenguang II Laser Upgraded Device) is blurred with uneven light radiation and has many scattered reference points, a novel algorithm of reference center extraction is proposed in this paper, which is based on position estimation and gradient extremum search. Firstly, all the reference points are determined...
Image segmentation in the big data context is a hot topic in the field of image understanding. Contrary to traditional computing paradigm with precise description of problems, Granular Computing (GrC) is studied by utilizing the toleration of imprecise, incomplete, uncertain and mass information to make systems manageable, robust, low-cost and harmonious. Thus it is an efficient measure to simplify...
Individual recognition is the technique which recognizes person's identity through his gait. Gait energy image (GEI) is a classical gait representation and it can be decomposed into structural part and detailed part. Then virtual gait energy image (VGEI) can be constructed in virtual space by integrating those two different parts. The generalized principal component analysis (GPCA) is applied to VGEI...
In order to detect the intrusion in the system, the information fusion technology was applied into intrusion detection. First, the audit data based on host and network data based on net were trained all together by using SVM and classification were realized. Then the D-S evidence theory was adopted to complete decision fusion. The performance of intrusion detection system is improved greatly, false...
Structure damage is a great threat to an uninterrupted operation of modern machines because it may cause catastrophic failures. Thus, damage detection has become the most important research topics. At present, a large number of damage detection methods have been proposed and applied to the field of structural damage detection, among which the most widely used detection methods are based on vibration...
Although the future mean of intracranial pressure (ICP) is of critical concern of many clinicians for timely medical treatment, the problem of forecasting the future ICP mean has not been addressed yet. In this paper, we present a nonlinear autoregressive with exogenous input artificial neural network based mean forecast algorithm (ANNNARX-MFA) to predict the ICP mean of the future windows based on...
In this paper, a new feature of surface electromyo-graphy (sEMG) by using discrete wavelet transform (DWT) is proposed for motion recognition of upper limbs, and this method can be eventually used for rehabilitation robot control. Seven traditional features of sEMG are also extracted for comparative study, they are integral of absolute value (IAV), difference absolute mean value (DAMV), zero crossing...
In this paper we addresses the problem of human action recognition by introducing a new representation of image sequences as a collection of spatiotemporal events that are localized at interest point and using multi-class SVM for classification. The interest points are detected by the SIFT detector and a spatio-temporal interest point detector. We proposed a new bag of words approach to represent...
In this article, we describe a system that estimates the position and orientation of a calibrated camera. For better estimation accuracy, artificial markers made up of infrared LEDs are placed in certain pattern onto the ceiling of a room. A 3D reconstruction process is first performed offline so that the coordinates of all LEDs within a unified world frame are determined. This process, based on incremental...
We propose a connected component labeling algorithm using line labeling and region growing method (LRGM) in this paper. First, we analyse the basic characteristic of current labeling algorithms, and set the scan order of LRGM from left to right, top to bottom, to assign a label to all connected components. Second, we eliminate label conflict by region growing method, because a large number of K label...
Sea-sky-line extraction under complicated sea-sky background is an important aspect of long-range target tracking research. An algorithm based on improved local complexity is proposed according to the feature that the sky and the sea usually show up at different gray levels in sea-sky background images. Median filter is applied first to remove peak noise, and then the point set of sea-sky-line region...
Text mining is an effective means of acquiring potentially useful knowledge from text document. However, traditional text mining cannot achieve high accuracy, because it cannot effectively make use of the semantic information of the text. Ontology provides theoretical basis and technical support for semantic information representation and organization. This paper introduces and analyzes text mining...
A text classification model based on Latent Semantic Analysis and Improved Hyper-sphere Support Vector Machine, is proposed in order to improve the accuracy and efficiency of text classification. Latent Semantic Analysis is used in this model for feature extraction, eliminating the text representation errors caused by synonyms and polysemes, and reducing the dimension of text vector. At the same time,...
Wavelet multiresolution analysis allows us to detect edges at different scales, also to obtain other important aspects of the extracted edges. However, due to the usual two-dimensional tensor product, wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture point-singularities, and the extracted edges are not continuous...
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