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4th International Conference on Manufacturing Science and Engineering (ICMSE 2013)

作者： Li, Caihua Zhang, Jinbo Hu, Xiaoping Zhao, Guofu Jiamusi Univ Coll Mech Engn Jiamusi Peoples R China Jilin Univ Key Lab Bionic Engn Minist Educ Changchun 130122 Peoples R China Agr & Sideline Prod Proc Machinery Res Inst Heilongjiang Jiamusi Peoples R China

ISBN: (纸本)9783037856932

With the rapid development of computer science, image processing, and pattern recognition, people are paying more and more attention on research and application of machine vision, which has resulted in excellent results in many fields. Depending on the features of untouched, fast-speed, real-time, proper precision, anti-interference, the inspection technology based on machine vision has been researched deeply and comprehensive applied aboard. Recently, the size measurement technology based on machine vision has been applied in the size measurement of the machine processing parts. A case study of typical regular mechanical parts, algorithm of position and size measurement of line, circle center and radius are researched, and good results are got, which established an academic foundation for further measurement of complex parts.

关键词： Machine vision Edge detection Size measurement

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Pooling in image representation: The visual codeword point of view

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computer vision AND IMAGE UNDERSTANDING 2013年第5期117卷 453-465页

作者： Avila, Sandra Thome, Nicolas Cord, Matthieu Valle, Eduardo Araujo, Arnaldo de A. Univ Paris 06 Sorbonne Univ LIP6 F-75005 Paris France Univ Fed Minas Gerais NPDI Lab DCC UFMG Belo Horizonte MG Brazil Univ Estadual Campinas RECOD Lab DCA FEEC UNICAMP Campinas SP Brazil

In this work, we propose Bossallova, a novel representation for content-based concept detection in images and videos, which enriches the Bag-of-Words model. Relying on the quantization of highly discriminant local descriptors by a codebook, and the aggregation of those quantized descriptors into a single pooled feature vector, the Bag-of-Words model has emerged as the most promising approach for concept detection on visual documents. Bossallova enhances that representation by keeping a histogram of distances between the descriptors found in the image and those in the codebook, preserving thus important information about the distribution of the local descriptors around each codeword. Contrarily to other approaches found in the literature, the non-parametric histogram representation is compact and simple to compute. Bossallova compares well with the state-of-the-art in several standard datasets: MIRFLICKR, ImageCLEF 2011, PASCAL VOC 2007 and 15-Scenes, even without using complex combinations of different local descriptors. It also complements well the cutting-edge Fisher Vector descriptors, showing even better results when employed in combination with them. Bossallova also shows good results in the challenging real-world application of pornography detection. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Image classification Image representation pattern recognition Bag-of-Words Visual dictionary Coding Pooling SVM

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Using Grammars for pattern recognition in Images: A Systematic Review

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ACM COMPUTING SURVEYS 2013年第2期46卷 26-26页

作者： Dias Pedro, Ricardo Wandre Nunes, Fatima L. S. Machado-Lima, Ariane Univ Sao Paulo Sch Arts Sci & Humanities Av Arlindo Bettio 1000 BR-03828000 Sao Paulo Brazil

Grammars are widely used to describe string languages such as programming and natural languages and, more recently, biosequences. Moreover, since the 1980s grammars have been used in computer vision and related areas. Some factors accountable for this increasing use regard its relatively simple understanding and its ability to represent some semantic pattern models found in images, both spatially and temporally. The objective of this article is to present an overview regarding the use of syntactic pattern recognition methods in image representations in several applications. To achieve this purpose, we used a systematic review process to investigate the main digital libraries in the area and to document the phases of the study in order to allow the auditing and further investigation. The results indicated that in some of the studies retrieved, manually created grammars were used to comply with a particular purpose. Other studies performed a learning process of the grammatical rules. In addition, this article also points out still unexplored research opportunities in the literature.

关键词： Algorithms Theory Image grammars computer vision image representation formal languages syntactic methods pattern recognition

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Investigating the effects of gender and age group based differences in identical twins

Investigating the effects of gender and age group based diff...

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National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Gayathri Mahalingam Karl Ricanek Institute of Interdisciplinary Science in Identity Sciences (Face Aging Group) University of North Carolina Wilmington NC

This work investigates feature-based techniques for component-face recognition on one of the most difficult tasks: recognition of identical twins. The challenge with solving face recognition for identical twins is to find a feature extraction and template formulation approach that sufficiently separates the identical twins in match space. This work extends this premise to investigate which components of the face (eye areas, nose, or mouth) are the most discriminative features. This work uses a patch-based feature extractor and compares it to two well-known texture techniques: LBP and HOG, for the full face and the component face. We show that a single face component, the eye area, nearly matches the performance of the full face and that a simple fusion of the components outperforms the full face face on the recognition task. Further we demonstrate that the proposed feature extractor does not exhibit gender biases as does some face recognition systems, i.e. it performs almost equally on males and females. And, finally we investigate the claims that face recognition becomes easier as the twins grow older. This work adds a final contribution by experimenting on the largest public identical twins corpora available to date: ND/WVU (2009, 2010, 2011) and the CASIA Twins Face Dataset.

关键词： Face Face recognition Databases Feature extraction Biometrics (access control) Accuracy computer vision

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Attribute-Based Detection of Unfamiliar Classes with Humans in the Loop

Attribute-Based Detection of Unfamiliar Classes with Humans ...

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IEEE Conference on computer vision and pattern recognition

作者： Catherine Wah Serge Belongie Department of Computer Science and Engineering University of California

ISBN: (纸本)9781467364102

Recent work in computer vision has addressed zero-shot learning or unseen class detection, which involves categorizing objects without observing any training examples. However, these problems assume that attributes or defining characteristics of these unobserved classes are known, leveraging this information at test time to detect an unseen class. We address the more realistic problem of detecting categories that do not appear in the dataset in any form. We denote such a category as an unfamiliar class;it is neither observed at train time, nor do we possess any knowledge regarding its relationships to attributes. This problem is one that has received limited attention within the computer vision community. In this work, we propose a novel approach to the unfamiliar class detection task that builds on attribute-based classification methods, and we empirically demonstrate how classification accuracy is impacted by attribute noise and dataset "difficulty," as quantified by the separation of classes in the attribute space. We also present a method for incorporating human users to overcome deficiencies in attribute detection. We demonstrate results superior to existing methods on the challenging CUB-200-2011 dataset.

关键词： Visualization Birds Training Accuracy Support vector machines computer vision Testing

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Fourth International Conference on Machine vision, ICMV 2011: computer vision and Image Analysis;pattern recognition and Basic Technologies

Fourth International Conference on Machine Vision, ICMV 2011...

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4th International Conference on Machine vision: computer vision and Image Analysis;pattern recognition and Basic Technologies, ICMV 2011

ISBN: (纸本)9780819490261

The proceedings contain 120 papers. The topics discussed include: research on the safety evaluation index of urban rail transit network operation;evaluation information integration model on book purchasing bids;a new distributed systems scheduling algorithm: a swarm intelligence approach;hardware architecture of OFCE-HS for hardware implementation;optimization of knowledge sharing through multi-forum using cloud computing architecture;a parallel encryption algorithm for dual-core processor based on chaotic map;a novel architecture for information retrieval system based on semantic web;investigating the effect of software project type on accuracy of software development effort estimation in COCOMO model;a comprehensive framework for detecting and tracking space objects;design and implementation of multilayer cache strategy of web system based on seam;and a proposed algorithm for solving fuzzy multi-objectives linear programming.

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基于计算机视觉的车载轨道巡检系统研制

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中国铁道科学 2013年第1期34卷 139-144页

作者：许贵阳史天运任盛伟韩强王登阳中国铁道科学研究院基础设施检测研究所北京100081 中国铁道科学研究院电子计算技术研究所北京100081

基于计算机视觉的车载轨道巡检系统由图像数据采集、数据分析和信息管理3个子系统组成;采用线阵相机进行1.6mm等间距运动扫描,并运用多线程交互和虚拟内存映射技术实现运动状态下轨道图像数据的采集和存储;在分析轨道图像病害特征的基础... 详细信息

基于计算机视觉的车载轨道巡检系统由图像数据采集、数据分析和信息管理3个子系统组成;采用线阵相机进行1.6mm等间距运动扫描,并运用多线程交互和虚拟内存映射技术实现运动状态下轨道图像数据的采集和存储;在分析轨道图像病害特征的基础上,运用主成分分析、线性判别分析和Adaboost等方法建立机器学习模型,实现对钢轨、扣件和道床3个区域病害的模式识别。应用验证表明:系统能够有效检出钢轨表面擦伤、扣件缺失和移位以及轨道板裂纹等病害,其中钢轨表面擦伤、扣件缺失的检出率达95%;能够代替传统的人工步行巡道,而且最高巡检速度可达160km.h-1。

关键词：轨道巡检计算机视觉线阵相机高速铁路

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Review of "Autonomous Intelligent Vehicles: Theory, Algorithms, and Implementation" (Cheng, H.;2011) [Book review]

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IEEE Intelligent Transportation Systems Magazine 2013年第3期5卷 74-76页

作者： Christos-Nikolaos Anagnostopoulos

This book summarizes his recent research work on Intelligent Vehicles. The target audience of the book is researchers, professionals and graduate students interested in a broad scientific field that includes not only basic principles, such as signal-image processing and pattern recognition, but also targeted fields of application, such as Intelligent Transportation Systems (ITS) and, more specifically, Intelligent Vehicles (IVs). The field of IVs includes a wide range of technologies spanning from vehicle dynamics to information, communications, hardware, computer vision, artificial intelligence, ergonomics and human factors.

关键词： Book reviews Intelligent vehicles Mobile robots Autonomic systems Machine intelligence

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基于计算机视觉的大田害虫远程自动识别系统

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农业工程学报 2013年第3期29卷 156-162页

作者：韩瑞珍何勇浙江大学生物系统工程与食品科学学院杭州310058 浙江传媒学院电子信息学院杭州310018 浙江大学唐仲英传感材料及应用研究中心杭州310058

为了实现大田害虫的快速实时识别和诊断,设计了一套大田害虫远程自动识别系统。该系统通过3G无线网络将害虫照片传输到主控平台中,在主控平台中实现远程自动识别。系统首先对害虫图像进行基于形态和颜色特征值的提取。害虫图像的形态特... 详细信息

为了实现大田害虫的快速实时识别和诊断,设计了一套大田害虫远程自动识别系统。该系统通过3G无线网络将害虫照片传输到主控平台中,在主控平台中实现远程自动识别。系统首先对害虫图像进行基于形态和颜色特征值的提取。害虫图像的形态特征由周长、面积、偏心率等以及7个胡不变矩共16个特征值组成,颜色特征值由9个颜色矩组成,然后建立支持向量机分类器。采用该系统对6种常见大田害虫进行了测试,平均准确率达到87.4%。考虑到不同的害虫姿态和大田中不同的光照条件,系统的分类效果是满意的。

关键词：计算机视觉图像处理监测大田害虫植保

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Multimodal Feature Fusion for Robust Event Detection in Web Videos

Multimodal Feature Fusion for Robust Event Detection in Web ...

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IEEE Conference on computer vision and pattern recognition (CVPR)

作者： Natarajan, Pradeep Wu, Shuang Vitaladevuni, Shiv Zhuang, Xiaodan Tsakalidis, Stavros Park, Unsang Prasad, Rohit Natarajan, Premkumar Raytheon BBN Technol Speech Language & Multimedia Business Unit Cambridge MA 02138 USA

ISBN: (纸本)9781467312288

Combining multiple low-level visual features is a proven and effective strategy for a range of computer vision tasks. However, limited attention has been paid to combining such features with information from other modalities, such as audio and videotext, for large scale analysis of web videos. In our work, we rigorously analyze and combine a large set of low-level features that capture appearance, color, motion, audio and audio-visual co-occurrence patterns in videos. We also evaluate the utility of high-level (i.e., semantic) visual information obtained from detecting scene, object, and action concepts. Further, we exploit multimodal information by analyzing available spoken and videotext content using state-of-the-art automatic speech recognition (ASR) and videotext recognition systems. We combine these diverse features using a two-step strategy employing multiple kernel learning (MKL) and late score level fusion methods. Based on the TRECVID MED 2011 evaluations for detecting 10 events in a large benchmark set of similar to 45000 videos, our system showed the best performance among the 19 international teams.

关键词： Web video Event detection Information retrieval systems-Teletext and videotex Videotapes Audio LOW LEVEL images computer vision

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