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3rd International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE)

作者： Cang, Guihua Yue, Jianping Hohai Univ Sch Earth Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9783038352587

Fusion of close range photogrammetry (CRP) and terrestrial laser scanning (TLS) technology has been a hot topic in the field of building reconstruction. There are many ways to realize the fusion of the two kind data. In this paper, we propose a method for 3D-2D data registration based on Scale Invariant Feature Transform (sift) algorithm and range intensity data. 3D terrestrial laser scanner and digital camera are different sensors, which will lead to large difference between intensity image (derived from range intensity data) and color image. The traditional image matching method can not apply to register these kind images. This paper focuses on studying the feasibility and practicability of sift algorithm on such different images matching. The result shows that the principal of sift method is suitable for the registration of the two kind images.

关键词： Image Registration Terrestrial Laser Scanning Intensity Image Color Image sift algorithm

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A Novel Retake Detection Using LCS and sift algorithm

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10th Pacific Rim Conference on Multimedia

作者： Cooharojananone, Nagul Putpuek, Narongsak Satoh, Shin'ichi Lursinsap, Chidchanok Chulalongkorn Univ Fac Sci Dept Math Adv Virtual & Intelligent Comp Ctr Bangkok 10330 Thailand Natl Inst Informat Tokyo 1018430 Japan

ISBN: (纸本)9783642104664

In this paper, a method to determine retake in rushes videos is proposed This method first, divides the video into shots, and then each shot that contains a single color, color hat or clapper board is eliminated In each remaining shot, the similarity between consecutive flames is calculated using a matching algorithm and then converted into a string sequence The similarity between two sequence is evaluated by the Longest Common Subsequence algorithm (LCS) This proposed sift - LCS looted method was applied to the TRECVID BBC rushes videos of 2007 and 2008 as a competence test The results support the notion that the proposed method provides a reasonably high degree of accuracy, and identifies the likely causes of pool accuracy lot further improvements

关键词： sift algorithm Sequence matching LCS Retake detection Object location extraction

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An Improved sift algorithm for Binocular Vision

An Improved SIFT Algorithm for Binocular Vision

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2012 IEEE 11th International Conference on Signal Processing(ICSP 2012)

作者： Chuanjun Liu Hui Chen Lijie Gao School of information science and engineering Shandong University

ISBN: (纸本)9781467321969

In this paper we proposes an improved sift algorithm of feature points matching, in order to improve the matching efficiency and 'real-time'. First, we use the classical sift algorithm to extract image features, when formatting the feature descriptor, we use the gradient normalized;Second, since the sift feature points detected a large number of feature points, and each is 128-dimension vector, but for the matching algorithm based on the Euclidean minimum distance measure, we have to calculate the Euclidean distance of a point and all the feature points from the right image, then ascending sort, which leads to low efficiency of algorithm. Based on optical imaging theory and the theory of binocular vision, by the coordinate of each feature point of the first image, we narrow the search range of the second image from two directions of row and column, on the basis of maintaining the matching accuracy, we improve the efficiency of the algorithm.

关键词： sift algorithm feature point detection gradient normalized feature point matching

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An Image Registration Method Based on Improved sift algorithm 7

An Image Registration Method Based on Improved SIFT Algorith...

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7th International Conference on Advanced Communication and Networking (ACN)

作者： Meng, Qingsong Lv, Zhihui Harbin Univ Sci & Technol Sch Automat Harbin Peoples R China

ISBN: (纸本)9781467379557

The purpose of this paper is to eliminate the mismatch points of image registration. Analyzing the sift algorithm and finding mismatch source, according to the source to develop solutions to eliminate the error matching points. And compared with the traditional sift registration results. In this paper, firstly do initial matching with sift algorithm, then use the feature of key points in spatial domain to eliminate the error matching, Finally, using RANSAC algorithm to do the final debugging. Experimental results show that the improved sift algorithm can better eliminate mismatch points.

关键词： image registration sift algorithm several-for-one matching ransac algorithm

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Target Recognition Based on sift algorithm for a Train Uncoupling Robot 31

Target Recognition Based on SIFT Algorithm for a Train Uncou...

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31st Chinese Control And Decision Conference (CCDC)

作者： Wang Jiaqi Wang Fangyong Yao Jianjun Zhao Yue Liu Ning Harbin Engn Univ Coll Mech & Elect Engn Harbin 150001 Peoples R China Northeast Forestry Univ Coll Engn & Technol Harbin 150001 Peoples R China

ISBN: (纸本)9781728101057

The train uncoupling robot is a 4-DOF robot which can complete the uncoupling work efficiently and accurately in the process of disassembly or marshalling of freight trains or passenger trains without the help of workers. The uncoupling work should be completed when the train and the uncoupling robot are both in motion. However, this increases the difficulty of recognizing the hook of trains and finishing the uncoupling work automatically. Therefore, the visual system of the robot plays a vital role during the uncoupling process so that it can be able to recognize the target hook by analyzing images and data from cameras and sensors. Furthermore, it should also have the ability to predict the motion planning of the object. In this paper, a visual control scheme is developed by using the Scale-invariant Feature Transform (sift) algorithm to recognize the hook of train in motion. It searches the extreme points as the key-points, and extracts the features such as position, scale and direction to match between the two images. The results indicate that the target hook can be recognized accurately and the recognition speed can meet the working requirements of the system by using the proposed visual control scheme even if the size of the target is varying or the target rotates moderately.

关键词： Train Uncoupling Robot Target Recognition sift algorithm Feature Descriptor

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Two Improved Methods of sift algorithm Combined with Harris

Two Improved Methods of SIFT Algorithm Combined with Harris

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24th Chinese Control and Decision Conference (CCDC)

作者： Shao Wei Li Na Sun Lijuan Sui Shulin Liu Xiangpeng Qingdao Univ Sci & Technol Coll Automat Elect & Engn Qingdao 266042 Peoples R China Qingdao Univ Sci & Technol Coll Mat Sci & Phys Qingdao 266061 Peoples R China

ISBN: (纸本)9781457720727

Due to the invariance of scale, rotation and illumination, sift algorithm is commonly used in image matching. According to Harris algorithm, two simplified methods of sift algorithm are developed to improve real-time efficiency and robustness of feature detection. In the stage of accurate keypoints localization, two improved methods are proposed to eliminate edge responses. One is the replacement of Hessian matrix by the local autocorrelation function of Harris;the other is using the measure of corner response function of the Hessian matrix. The experimental results show that the improved methods can increase the performance of sift algorithm.

关键词： sift algorithm Harris algorithm The Hessian matrix

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Vehicle image mosaics technology based on improved sift algorithm 13

Vehicle image mosaics technology based on improved SIFT algo...

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2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)

作者： Wang Peng Duan Yichen Dong Mianmian Xiong Miaomiao Li Xue School of Electronics and Information Engineering Xi'an Technological University

ISBN: (纸本)9781509050369;9781509050352

Aimed at the problem of large vehicle outline detect in the field of intelligent traffic, this paper proposes a vehicle stitching algorithm based on improved sift feature matching to reduce the requirements of the camera configuration and choose camera position easily. Firstly, the improved sift algorithm is used to extract and match feature point quickly. So the superior characteristics of sift algorithm is utilized to not only deal with the image's rotation, translation and illumination changes, the stability of visual change and affine transformation, but also ensure the processing speed of algorithm by reducing the complexity of the sift algorithm. In this paper, mismatched points are simply and quickly removed by limiting the matching line slope, which is proved to be a good result. After obtaining the stable matching points, we calculate the transformation matrix between two images. Finally, the image pyramid fusion is performed to perfect our stitching image and this pixel level processing has a good ability to eliminate fusion mosaic slot caused by camera position deviation, different light and other causes. Experiment results show that this algorithm reduces the rate of mismatching and improves the low efficiency in traditional image mosaic. The improved sift algorithm has distinct advantage in increasing speed, obtaining high resolution and completing vehicle images after mosaic.

关键词： sift algorithm Feature points matching

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Asphalt Pavement texture 3D Reconstruction Based on Binocular Vision System with sift algorithm

Asphalt Pavement texture 3D Reconstruction Based on Binocula...

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International Conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Ran, Maoping Xiao, Shenqing Zhou, Xinglin Xiao, Wangxin Wuhan Univ Sci & Technol Sch Automobile & Traff Engn Wuhan 430081 Hubei Peoples R China Minist Transport Res Inst Highway Beijing 100088 Peoples R China

ISBN: (纸本)9781538628133

Collecting 3D micro-texture of asphalt pavement is the key work of studying the constitutive relationship between asphalt pavement micro-texture and pavement performance. Due to affine characteristics of asphalt pavement micro texture, it is very difficult to obtain 3D micro-texture quickly and accurately. The paper provided a 3D reconstruction method for asphalt pavement by establishing 3D mathematical measuring model of binocular vision. The camera interior and exterior parameters was obtained by camera calibration;Homograph II was calculated by feature points extraction and matching with the help of sift algorithm, then realized area points matching, finally the asphalt pavement micro-texture 3D image reconstruction was achieved based on the parameters and area-point coordinates. The reconstruction results show that using binocular vision method to extract the 3D image micro-texture is feasible and rapid, it is potential to acquire a large area 3D reconstruction of asphalt pavement micro-texture with the help of homograph.

关键词： 3D-image reconstruction binocular vision pavement texture sift algorithm stereo matching

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Ice Velocity in Upstream of Heilongjiang Based on UAV Low-Altitude Remote Sensing and the sift algorithm

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WATER 2022年第12期14卷 1957-1957页

作者： Wang, Enliang Hu, Shengbo Han, Hongwei Li, Yuang Ren, Zhifeng Du, Shilin Northeast Agr Univ Sch Water Conservancy & Civil Engn Harbin 150030 Peoples R China Heilongjiang Prov Key Lab Water Resources & Water Harbin 150030 Peoples R China

In river management, it is important to obtain ice velocity quickly and accurately during ice flood periods. However, traditional ice velocity monitoring methods require buoys, which are costly and inefficient to distribute. It was found that UAV remote sensing images combined with machine vision technology yielded obvious practical advantages in ice velocity monitoring. Current research has mainly monitored sea ice velocity through GPS or satellite remote sensing technology, with few reports available on river ice velocity monitoring. Moreover, traditional river ice velocity monitoring methods are subjective. To solve the problems of existing time-consuming and inaccurate ice velocity monitoring methods, a new ice velocity extraction method based on UAV remote sensing technology is proposed in this article. In this study, the Mohe River section in Heilongjiang Province was chosen as the research area. High-resolution orthoimages were obtained with a UAV during the ice flood period, and feature points in drift ice images were then extracted with the scale-invariant feature transform (sift) algorithm. Moreover, the extracted feature points were matched with the brute force (BF) algorithm. According to optimization results obtained with the random sample consensus (RANSAC) algorithm, the motion trajectories of these feature points were tracked, and an ice displacement rate field was finally established. The results indicated that the average ice velocities in the research area reached 2.00 and 0.74 m/s, and the maximum ice velocities on the right side of the river center were 2.65 and 1.04 m/s at 16:00 on 25 April 2021 and 8:00 on 26 April 2021, respectively. The ice velocity decreased from the river center toward the river banks. The proposed ice velocity monitoring technique and reported data in this study could provide an effective reference for the prediction of ice flood disasters.

关键词： unmanned aerial vehicles sift algorithm brutal force matching RANSAC algorithm ice velocity

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Panorama Stitching Based on sift algorithm and Levenberg-Marquardt Optimization

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Physics Procedia 2012年 33卷 811-818页

作者： ZHONG Min ZENG Jiguo XIE Xusheng College of Computer Information Engineering Jiangxi Normal University Nanchang China

Panorama stitching algorithm based on scale invariant feature transform and Levenberg-Marquardt optimiza-tion is proposed. Mapping the source planar images to a cylind-rical surface is the first step. Then, correct matching feature pairs are detected between two images by sift and RANSAC algorithm. Finally the Levenberg-Marquardt algorithm is used for calculating the initial estimates of motion parameters. Experiment results show that this method is effective against the hand-held camera motion with small rotation around the optical axis, small horizontal and vertical movement.

关键词： panorama cylindrical projection sift algorithm Levenberg-Marquardt Optimization

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