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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

共 1407 条记录，以下是781-790 订阅

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Poster: A Real-time Cattle Recognition System using Wireless Multimedia Networks 14

Poster: A Real-time Cattle Recognition System using Wireless...

引用

14th Annual international conference on Mobile Systems, Applications, and Services (MobiSys)

作者： Kumar, Santosh Singh, Sanjay Kumar Dutta, Tanima Gupta, Hari Prabhat Indian Inst Technol BHU Varanasi Varanasi Uttar Pradesh India

ISBN: (纸本)9781450344166

In this paper, we propose a cattle recognition system using wireless multimedia networks. The images are captured and transferred them to the server using Wi-Fi technology. The system performs image pre-processing on the muzzle point image of cattle to mitigate and filter the noise. The system uses support vector machine to classify the extracted feature of the muzzle images of cattle. We use a similarity score measurement for matching the muzzle points with the database. We also developed a prototype for evaluating the accuracy of the system.

关键词： pattern recognition support vector machine animal biometrics image processing muzzle point pattern cattle recognition computer vision

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Smoke detection prescreening in sequential images 31

Smoke detection prescreening in sequential images

引用

31st international conference on computers and Their Applications, CATA 2016

作者： Olson, Andrew M. Stanton, Harrison Egbert, Dwight D. Rojas, Raul Nicolescu, Mircea Harris, Frederick C. Computer Science and Engineering University of Nevada Reno RenoNV United States

ISBN: (纸本)9781943436026

This paper investigates the use and optimization of particular image processing techniques as applied to the problem of early detection of smoke in chronologically sequential images taken in nominally undeveloped regions. In particular, we are studying techniques used to eliminate as many potential regions in the image from detailed investigation by other means in the vision processing pipeline. This work is intended to reduce the sophistication necessary to eliminate or confirm the presence of smoke in these images, either by automated or human means. Copyright ISCA.

关键词： Smoke

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Automatic System for Zebrafish Counting in Fish Facility Tanks 13th

Automatic System for Zebrafish Counting in Fish Facility Tan...

引用

13th international conference on image Analysis and Recognition in Memory of Mohamed Kamel (ICIAR)

作者： Silverio, Francisco J. Certal, Ana C. de Ferro, Carlos Mao Monteiro, Joana F. Cruz, Jose Almeida Ribeiro, Ricardo Silva, Joao Nuno Univ Lisbon Inst Super Tecn INESC ID Lisboa Lisbon Portugal Champalimaud Ctr Unknown Lisbon Portugal

ISBN: (纸本)9783319415017;9783319415000

In this project we propose a computer vision method, based on background subtraction, to estimate the number of zebrafish inside a tank. We addressed questions related to the best choice of parameters to run the algorithm, namely the threshold blob area for fish detection and the reference area from which a blob area in a threshed frame may be considered as one or multiple fish. Empirical results obtained after several tests show that the method can successfully estimate, within a margin of error, the number of zebrafish (fries or adults) inside fish tanks proving that adaptive background subtraction is extremely effective for blob isolation and fish counting.

关键词： computer vision Zebrafish counting Background subtraction Hu moments image processing

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A FAST ADAPTIVE SPATIO-TEMPORAL 3D FEATURE FOR VIDEO-BASED PERSON RE-IDENTIFICATION 23

A FAST ADAPTIVE SPATIO-TEMPORAL 3D FEATURE FOR VIDEO-BASED P...

引用

23rd IEEE international conference on image processing (ICIP)

作者： Liu, Zheng Chen, Jiaxin Wang, Yunhong Beihang Univ Sch Comp Sci & Engn Lab Intelligent Recognit & Image Proc Beijing 100191 Peoples R China

ISBN: (纸本)9781467399616

Video-based person re-identification has become a hot topic in the field of research on computer vision and intelligent surveillance, which is more robust to the variations in a person's appearance than single-shot based methods and involves space-time information. However, the most existing spatio-temporal features have been proposed for action recognition that they mainly focus on the exact spatial changes over time. Unlike action recognition, pedestrians captured in person re-identification problem show similar and cyclic walking activities. The essential spatio-temporal information for person re-identification is the statistical information over time. In this paper, we propose a novel spatio-temporal feature, namely Fast Adaptive Spatio-Temporal 3D feature (FAST3D), for video-based person re-identification. The feature is able to extract the statistical motion information based on densely computed multi-direction gradients and an adaptive fusion process. We evaluate our method on two challenging datasets and the experimental results show the effectiveness and efficiency of the proposed feature.

关键词： Person re-identification spatio-temporal feature efficient computation relevance metric learning

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Perceptual Hash image Classification Algorithm based on SIFT Feature

Perceptual Hash Image Classification Algorithm based on SIFT...

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2017 2nd international conference on Mechatronics and Information Technology(ICMIT 2017)

作者： Xi Li Bin Tian Nan Xu School of Electrical and Information Engineering Wuhan Institute of Technology

image classification with wide application in computer vision refers to an image processing method which classifies different categories of goals based on different features reflected in image information. BOW-SVM is a typical image classification method with higher accuracy but unsatisfactory operating performance. To improve performance and accuracy more effectively, an efficient image classification method based on HOG-PCA is presented. First, extract and whiten features of histogram of oriented gradients(HOG), then make down sampling randomly to unify scale, and then make feature mapping through principal component analysis(PCA), and finally make nearest neighbor classification through least second norm determination. C++ is adopted in the experiment where extraction is made through OPENCV and Darwin and test is made in the PASCAL 2012 dataset, and the experiment compares accuracy and operating performance of this method and BOW-SVM, proving that the presented method is more efficient and of better operating performance.

关键词： HOG Least Second Norm PCA image Classification image Feature

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Quality Evaluation of Apple Fruit for Automated Food processing 1st

Quality Evaluation of Apple Fruit for Automated Food Process...

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1st international conference on Smart Trends for Information Technology and computer Communications (SmartCom)

作者： Komal, Sindhi Pandya, Jaymit Vegad, Sudhir GH Patel Coll Engn & Technol Anand Gujarat India AD Patel Inst Technol Anand Gujarat India

ISBN: (纸本)9789811034336;9789811034329

Quality inspection of fruits with help of computer vision or image processing is gaining much attention nowadays because of the costly and labor intensive techniques used earlier. It has been proven much useful to the agricultural sectors and other industries in the past. The present research work is based on the quality evaluation of apple fruit. Since less work is done for the quality evaluation of internal part of apple, i.e. slices, here the experiment will be done;first on the external surface and then on the slices. Here hue histogram intersection is used for external surface defect detection and for slices defect checking;features called Color Coherence Vector and Complete Local Binary Patterns are extracted from the slice images and they are given as input to Multi-Class Support Vector Machine classifier. Both linear and nonlinear SVMs were used and linear classification gave better results.

关键词： Digital image processing Quality evaluation Apple disease Feature extraction Classification Apple slice Color Coherence Vector computer vision Complete local binary patterns

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Robust image Matching Using Local Affine Region And Mahalanobis Metric 13

Robust Image Matching Using Local Affine Region And Mahalano...

引用

13th IEEE international conference on Signal processing (ICSP)

作者： Ye, Zupei Tang, Linbo Zhao, Baojun Beijing Inst Technol Sch Informat & Elect Beijing Peoples R China

ISBN: (纸本)9781509013456

image matching plays an essential role in various computer vision applications. Recent researches found that relative positions among a feature point and its local neighbors can be utilized to build a K Nearest Neighbors (KNN) graph to eliminate the matches with geometric inconsistency. However, the existing KNN graph construction method is unstable under viewpoint changes, as the used Euclidean metric cannot accurately reflect the spatial relationship of feature points. In order to solve this problem, this paper proposes a robust image matching algorithm by using local affine regions and Mahalanobis metric. First, feature points from the images are detected not only with the coordinates but also affine regions around them. Next, feature points and affine information is used to build KNN graph for each image under Mahalanobis metric. Finally, the mismatches are eliminated via finding consensus subgraph. Experimental results demonstrate that the proposed algorithm can build robust KNN graph under large viewpoint changes and achieve higher matching accuracy.

关键词： image matching affine region graph model Mahalanobis metric

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3D sensor-based Moving Human Tracking Robot with Obstacle Avoidance

3D sensor-based Moving Human Tracking Robot with Obstacle Av...

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IEEE international Multidisciplinary conference on Engineering Technology (IMCET)

作者： Ahmad, Abdel-Mehsen Al Youssef, Hiba Lebanese Int Univ Dept Comp & Commun Engn Sch Engn Beirut Lebanon

ISBN: (纸本)9781509052813

This paper, represents a design constituting of a robot that uses an Arduino to drive motors enabling it to move around the room in a direction determined by a processing sketch that uses the Kinect to scan the room and determine where the robot should move. The design works by tracking the center of mass of a human having a skeleton, and avoiding obstacles that interfere it` s movement. The approach used in this system is attaching the computer and Kinect to the robot so that its vision system can move along with it as it explores the space. To accomplish this, a toy car was used as a robot in order to support the weight of a laptop or other small computer as well as the Kinect.

关键词： Kinect Arduino Robot Depth image Tracking Obstacle Avoidance

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A Haze Density Aware Adaptive Perceptual Single image Haze Removal Algorithm

A Haze Density Aware Adaptive Perceptual Single Image Haze R...

引用

IEEE international conference on Information and Automation (ICIA)

作者： He, Chuanzi Zhang, Chendi Cheng, Qingrong Jin, Xixiaoyi Yin, Jianjun Fudan Univ Dept Elect Engn Sch Informat Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9781509041022

Haze or fog jeopardizes both environment and image quality, which degrades the quality of subsequent computer vision algorithms. Recently haze removal method in image processing makes significant progress. The existing methods usually require complicated manual parameters setting according to the variance of input. Among them, dehazing method based on dark channel prior is considered to be the most efficient one. However, the problems brought by dark channel prior method including low luminance, sky region distortion and low saturation are inevitable. The proposed dehaze method in this paper can adaptively adjust parameters settings by introducing haze density detection. Besides, the proposed method improves the original dim recovered image by adaptively adjust exposure and color saturation in YCbCr color space. Furthermore, fast guided filter is employed to refine the transmission map. The experimental results show that the proposed method performs better both objectively and subjectively.

关键词： image dehazing haze removal haze density prediction perceptual image processing

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Selfie search: image retrieval and face recognition in iOS 3

Selfie search: Image retrieval and face recognition in iOS

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3rd international Symposium on computer vision and the Internet, visionNet 2016

作者： Marques, Oge Carson, Joseph Florida Atlantic University 777 Glades Rd Boca RatonFL United States

ISBN: (纸本)9781450343015

This paper describes the design and development of an iOS app for selfie search, which combines face detection and recognition capabilities with content-based image retrieval techniques. The app works offline, since all processing takes place entirely on the device. It was implemented in Objective-C and it leverages functionality from Apple's Core image API for image processing tasks and CouchbaseLite for the database layer. For face recognition, the app employs local binary patterns - encoded as spatially enhanced histograms, with weight maps that indicate preferred areas within the cropped image containing the face. The source code is available on GitHub. © 2016 ACM.

关键词： Face recognition

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