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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

共 1671 条记录，以下是961-970 订阅

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A directional-progressive search method for infrared small target detection 3

A directional-progressive search method for infrared small t...

引用

3rd Optoelectronics Global conference, OGC 2018

作者： Zhang, Xiangyue Ding, Qinghai Luo, Haibo Hui, Bin Chang, Zheng Zhang, Junchao Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China Space Star Technology Co. Ltd Beijing100086 China

ISBN: (纸本)9781538673973

Infrared small target detection plays a key role in infrared precision guidance and infrared early-warning system. It has been a difficult problem for researchers to study on how to detect targets accurately at a long distance as early as possible. Most of the existing algorithms can detect small targets in simple backgrounds, but they would fail on the detection when the background clutters are chaotic and the signal to clutter ratio (SCR) is low. Therefore, we propose a new infrared small target detection method which called a directional-progressive search (DPS) method. Our method derives from a fact that a small target is an isotropic Gaussian distribution at a long distance, while clutters show different characteristics in different directions. Based on this difference, we decompose the original image into first-order sub-images with different directions by using a first-order directional derivative (FODD) filter. Then zero-crossing points are detected in each direction step by step to distinguish small targets and background clutters. After screening progressively, the positions where existing zero-crossing points in every sub-image can be confirmed as targets. Experimental results show that our method acquires higher detection rates and lower false alarm rates compared with other methods. At the same time, our method can still keep better performance under various complex backgrounds. The robustness of our method is strong. © 2018 IEEE.

关键词： Clutter (information theory)

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image processing System for Automatic Segmentation and Yield Prediction of Fruits using Open CV 3

Image Processing System for Automatic Segmentation and Yield...

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3rd international conference on Current Trends in computer, Electrical, Electronics and Communication, CTCEEC 2017

作者： Gayathri Devi, T. Neelamegam, P. Sudha, S. ECE School of EEE SRC SASTRA University India EI School of EEE SASTRA University India

ISBN: (纸本)9781538632420

In fruit harvesting systems, automatic yield counting of fruits becomes a big issue. image processing techniques minimizes the manual task of recognizing and counting the fruits. In this paper, an image processing system for automatic segmentation and yield prediction of fruits is proposed on the basis of color and shape features is being performed. Initially the preprocessing is done on input fruit tree images. Then it is converted from RGB to HSV color space to detect the fruit region from its background. Color thresholding is used to mask the desired colors. Gaussian filter is used to remove noise. The contour of the image is taken. Then these images are processed by image processing algorithm. Color and shape based counting of fruit is presented at the output. The edge detection and combination of a circular fitting algorithm is applied for the automatic segmentation and automatic counting of fruits in the image. Different types of fruits (orange/tangerine, pomegranate, apple, lemon, mango, cherry) are used for automatic counting. Open CV Python software is used to perform the required image processing operations. © 2017 IEEE.

关键词： Edge detection

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An Efficient Way to Estimate the Focus of Expansion

An Efficient Way to Estimate the Focus of Expansion

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international conference on image, vision and Computing (ICIVC)

作者： Rui Huang Stefan Ericson School of Computer Science Nanjing University of Posts and Telecommunications Nanjing City China Department of Engineering University of Skvde Skovde Sweden

The following topics are dealt with: feature extraction; image segmentation; learning (artificial intelligence); image classification; object detection; image colour analysis; computer vision; image reconstruction; me... 详细信息

ISBN: (纸本)9781538649923

关键词： Cameras Optical flow computer vision Standards Motion detection image motion analysis Fitting

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3D Point Cloud Matching Based on Its 2D Representation for Visual Odometry 3

3D Point Cloud Matching Based on Its 2D Representation for V...

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3rd IEEE international conference on image processing, Applications and Systems (IPAS)

作者： Ko, Sanghyun Lee, Sukhan Sungkyunkwan Univ Coll Informat & Commun Engn Intelligent Syst Res Inst Suwon South Korea

ISBN: (纸本)9781728102474

Fast and accurate pose estimation of non-textured 3D objects based on 3D point cloud is emerged as important for the application of vision to industrial automation. There have been proposed a number of global and local 3D geometric features that can be extracted from 3D point cloud. However, they are either too inefficient or too inaccurate to be viable. In this paper, we presents a fast and accurate method of 3D pose estimation based on transforming 3D point cloud into 2D image, where the azimuth and elevation angles of as well as the distance to 3D points are converted to 2D pixels and their image intensities, respectively. The experiments show that the proposed method provides faster and more accurate 3D pose estimation, two orders of magnitude and over 25% of improvements in processing time and accuracy, respectively, compared to a top performance conventional 3D geometric feature based approach.

关键词： 3D Object 3D Point Cloud Pose Estimation Global Feature

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Sparse 3D Point-Cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation 1

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3rd international conference on Interactive Collaborative Robotics (ICR)

作者： Bokovoy, Andrey Yakovlev, Konstantin RUDN Univ Peoples Friendship Univ Russia Moscow Russia Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow Russia Natl Res Univ Higher Sch Econ Moscow Russia

ISBN: (数字)9783319995823

ISBN: (纸本)9783319995823;9783319995816

The monocular vision-based simultaneous localization and mapping (vSLAM) is one of the most challenging problem in mobile robotics and computer vision. In this work we study the post-processing techniques applied to sparse 3D point-cloud maps, obtained by feature-based vSLAM algorithms. Map post-processing is split into 2 major steps: (1) noise and outlier removal and (2) upsampling. We evaluate different combinations of known algorithms for outlier removing and upsampling on datasets of real indoor and outdoor environments and identify the most promising combination. We further use it to convert a point-cloud map, obtained by the real UAV performing indoor flight to 3D voxel grid (octo-map) potentially suitable for path planning.

关键词： 3D Point-cloud Outlier removal Upsampling vSLAM 3D path planning Sparse map Feature-based vSLAM

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Target Measurement in Elliptical Orbit Using Generalized Voxel Coloring 10

Target Measurement in Elliptical Orbit Using Generalized Vox...

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10th international conference on Digital image processing (ICDIP)

作者： Huang, Huimin Zhou, Zuofeng Guo, Huinan Cao, Jianzhong Chinese Acad Sci Xian Inst Opt & Precis Mech Xinxi Rd Xian 710119 Shaanxi Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (数字)9781510622005

ISBN: (纸本)9781510622005

Measurement of 3D scene from image sequences is necessary for many computer vision applications. In this paper, we identify the volumetric scene reconstruction as a critical issue for target measurement and use the statistical method to estimate the size of the reconstructed target. The proposed approach unifies the view volume in volumetric scene reconstruction while we only know the location information of the camera relative to the target in elliptical orbit. Experimental results on elliptical orbit with 200 meters long axis and 100 meters short axis illustrate that the average error is about 44 millimeters, which meets the accuracy requirement of general measurement.

关键词： Measurement Elliptical Orbit Generalized Voxel Coloring

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A vision-Based Strategy to Segment and Localize Ancient Symbols Written in Stone

A Vision-Based Strategy to Segment and Localize Ancient Symb...

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3rd Iberian Robotics conference (Robot)

作者： Duque-Domingo, Jaime Javier Herrera, P. Cerrada, Carlos Cerrada, Jose A. UNED ETSI Informat Dept Ingn Software & Sistemas Informat C Juan del Rosal 16 Madrid 28040 Spain

ISBN: (纸本)9783319708362;9783319708355

This work proposes an automatic method to detect ancient symbols written in stone. The proposed method takes into account well-known techniques used in computer vision to identify the contour of the symbols in the image. The two-stage method consists of segmentation and localization processes. Segmentation process includes a pre-processing step, edge detection and thresholding. Localization process is based on two conditions that take into account several parameters, like the distance between points, and the orientation and the continuity of the edges. This proposal has been applied to localize Egyptian cartouches (borders enclosing the name of a king) and stonemason's marks from images obtained under varying lighting conditions (controlled and natural lighting). The proposed method is compared favorably against other methods based on chain coding, neural networks and statistical correlation. The promising results give new possibilities to identify and recognize complex symbols and ancient texts.

关键词： image segmentation Edge detection Object localization

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Moving Object Detection Based on 3D Total Variation and Weighted Nonconvex Nuclear Norm 10

Moving Object Detection Based on 3D Total Variation and Weig...

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10th international conference on Digital image processing (ICDIP)

作者： Zhao, Wenzheng Cui, Qingqing Chen, Youguang East China Normal Univ Sch Comp Sci & Software Engn 3663 North Zhongshan Rd Shanghai 200062 Peoples R China

ISBN: (数字)9781510622005

ISBN: (纸本)9781510622005

Moving object detection and background estimation are important steps in numerous computer vision applications. Low rank and sparse representation based methods have attracted wide attention in background modeling field. However, many existing methods ignore the spatio-temporal information of the foreground. In this paper, a new low-rank and sparse representation model for moving object detection is proposed, in which we regard the image sequence as being made up of the sum of a low-rank static background matrix, a sparse foreground matrix and a sparser dynamic background matrix. The 3D total variation regularizer and weighted nonconvex nuclear norm are incorporated to refine our model. Extensive experiments on challenging datasets demonstrate that our method works effectively and outperforms many state-of-the-art approaches.

关键词： moving object detection low-rank modeling 3D total variation weighted nonconvex nuclear norm

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Object of Interest Segmentation in Video Sequences with Gaze Data 3

Object of Interest Segmentation in Video Sequences with Gaze...

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3rd IEEE international conference on image processing, Applications and Systems (IPAS)

作者： Krieger, Laura Heidemann, Gunther Schoening, Julius Osnabruck Univ Inst Cognit Sci Osnabruck Germany

ISBN: (纸本)9781728102474

Object of Interest (OoI) segmentation in video sequences is, due to its temporal and spatial complexity, still a difficult task. Thus, it cannot be done automatically, and interactive segmentation methods are inconvenient and time-consuming. Overcoming these drawbacks and performing OoI segmentation in real-time, this paper introduces a new approach for gaze-based OoI segmentation. The user fixates on the OoI throughout watching a video sequence. The users' gaze provides relevant information on the location of the OoI, which is then used for segmenting the OoI. In comparison to present segmentation methods, our approach notably reduced user-interactions required to attain pixel-accurate segmentations. The first evaluation of our gaze-based OoI segmentation method shows promising results. These are close to, and sometimes even exceeding the quality of the polygon-based ground truth segmentation. In conclusion, these findings encourage further exploration of gaze-based OoI segmentation.

关键词： Eye Tracking Gaze-Based Interaction Human-computer Interaction Video Segmentation

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Object segmentation using graph cuts and active contours in a pyramidal framework 3

Object segmentation using graph cuts and active contours in ...

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3rd international conference on Photonics Solutions (ICPS)

作者： Subudhi, Priyambada Mukhopadhyay, Susanta Indian Sch Mines Indian Inst Technol Dhanbad Bihar India

ISBN: (数字)9781510619951

ISBN: (纸本)9781510619951

Graph cuts and active contours are two very popular interactive object segmentation techniques in the field of computer vision and image processing. However, both these approaches have their own well-known limitations. Graph cut methods perform efficiently giving global optimal segmentation result for smaller images. However, for larger images, huge graphs need to be constructed which not only takes an unacceptable amount of memory but also increases the time required for segmentation to a great extent. On the other hand, in case of active contours, initial contour selection plays an important role in the accuracy of the segmentation. So a proper selection of initial contour may improve the complexity as well as the accuracy of the result. In this paper, we have tried to combine these two approaches to overcome their above-mentioned drawbacks and develop a fast technique of object segmentation. Here, we have used a pyramidal framework and applied the mincut/maxflow algorithm on the lowest resolution image with the least number of seed points possible which will be very fast due to the smaller size of the image. Then, the obtained segmentation contour is super-sampled and and worked as the initial contour for the next higher resolution image. As the initial contour is very close to the actual contour, so fewer number of iterations will be required for the convergence of the contour. The process is repeated for all the high-resolution images and experimental results show that our approach is faster as well as memory efficient as compare to both graph cut or active contour segmentation alone.

关键词： Graph cuts Active contours image pyramid

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