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A deep network model based on subspaces: A novel approach for image classification 基于子空间的深度网络模型:一种新的图像分类方法
IAPR International Workshop on Machine Vision Applications Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986894
B. Gatto, L. S. Souza, E. Santos
{"title":"A deep network model based on subspaces: A novel approach for image classification","authors":"B. Gatto, L. S. Souza, E. Santos","doi":"10.23919/MVA.2017.7986894","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986894","url":null,"abstract":"In this paper, we propose a novel deep neural network based on learning subspaces and convolutional neural network with applications in image classification. Recently, multistage PCA based filter banks have been successfully adopted in convolutional neural networks architectures in many applications including texture classification, face recognition and scene understanding. These approaches have shown to be powerful, with a straightforward implementation that enables a fast prototyping of efficient image classification systems. However, these architectures employ filters based on PCA, which may not achieve high discriminative features in more complicated computer vision datasets. In order to cope with the aforementioned drawback, we propose a Hybrid Subspace Neural Network (HS-Net). The proposed architecture employs filters from both PCA and discriminative filters banks from more sophisticated subspace methods, therefore achieving more representative and discriminative information. In addition, the use of hybrid architecture enables the use of supervised and unsupervised samples, depending on the application, making the introduced architecture quite attractive in practical terms. Exsperimental results on three publicly available datasets demonstrate the effectiveness and the practicability of the proposed architecture.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115496942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Query-by-Sketch Image Retrieval Using Edge Relation Histogram 基于边缘关系直方图的逐草图查询图像检索
IAPR International Workshop on Machine Vision Applications Pub Date : 2013-02-01 DOI: 10.1587/TRANSINF.E96.D.340
Y. Kumagai, T. Arikawa
{"title":"Query-by-Sketch Image Retrieval Using Edge Relation Histogram","authors":"Y. Kumagai, T. Arikawa","doi":"10.1587/TRANSINF.E96.D.340","DOIUrl":"https://doi.org/10.1587/TRANSINF.E96.D.340","url":null,"abstract":"In the Query-by-sketch image retrieval, feature extraction method is important, because the retrieval result depend on image feature. In this paper, we propose the query-by-sketch image retrieval using Edge Relation Histogram (ERH) as global and local feature. ERH focuses on the relation among edge pixels, and ERH is shift-, scale-, rotation- and symmetry-invariant feature. This method was applied to 20,000 images in Corel Photo Gallery. Experimental results show that the proposed method is effective in retrieving images.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122406330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Static Estimation of the Meteorological Visibility Distance in Night Fog with Imagery 利用图像静态估计夜雾气象能见度距离
IAPR International Workshop on Machine Vision Applications Pub Date : 2010-07-01 DOI: 10.1587/TRANSINF.E93.D.1780
Romain Gallen, N. Hautière, E. Dumont
{"title":"Static Estimation of the Meteorological Visibility Distance in Night Fog with Imagery","authors":"Romain Gallen, N. Hautière, E. Dumont","doi":"10.1587/TRANSINF.E93.D.1780","DOIUrl":"https://doi.org/10.1587/TRANSINF.E93.D.1780","url":null,"abstract":"In this paper, we propose a new way to estimate fog extinction at night using a classification of fog depending on the forward scattering. We show that a characterization of fog based on the atmospheric extinction parameter only is not sufficient. This method works in dense fogs (meteorological visibility distances < 400m) with a single image and three known light sources. The method is validated on synthetic images generated with a semi Monte-Carlo ray tracing software dedicated to fog simulation. We drove this study in simulated environment in order to help us designing a test site located outdoor.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126589028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Probabilistic BPRRC: Robust Change Detection against Illumination Changes and Background Movements 概率BPRRC:针对光照变化和背景运动的鲁棒变化检测
IAPR International Workshop on Machine Vision Applications Pub Date : 2010-07-01 DOI: 10.1587/TRANSINF.E93.D.1700
K. Yokoi
{"title":"Probabilistic BPRRC: Robust Change Detection against Illumination Changes and Background Movements","authors":"K. Yokoi","doi":"10.1587/TRANSINF.E93.D.1700","DOIUrl":"https://doi.org/10.1587/TRANSINF.E93.D.1700","url":null,"abstract":"This paper presents PrBPRRC (Probabilistic Bipolar Radial Reach Correlation), a change detection method that is robust against illumination changes and background movements. Most of the traditional change detection methods are robust against either illumination changes or background movements; BPRRC is one of the illumination-robust change detection methods. We introduce a probabilistic background texture model into BPRRC and add the robustness against background movements and foreground invasions such as moving cars, walking pedestrians, swaying trees , and falling snow. We show the superiority of our PrBPRRC under the environment with illumination changes and background movements by using public datasets: ATON Highway data, Karlsruhe traffic sequence data, and PETS 2007 data.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132804570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
View-invariant Human Action Recognition Based on Factorization and HMMs 基于因子分解和hmm的视觉不变人体动作识别
IAPR International Workshop on Machine Vision Applications Pub Date : 2008-07-01 DOI: 10.1093/ietisy/e91-d.7.1848
Xi Li, K. Fukui
{"title":"View-invariant Human Action Recognition Based on Factorization and HMMs","authors":"Xi Li, K. Fukui","doi":"10.1093/ietisy/e91-d.7.1848","DOIUrl":"https://doi.org/10.1093/ietisy/e91-d.7.1848","url":null,"abstract":"This paper addresses the problem of view invariant action recognition using 2D trajectories of landmark points on human body. It is a challenging task since for a specific action category, the 2D observations of different instances might be extremely different due to varying viewpoint and changes in speed. By assuming that the execution of an action can be approximated by dynamic linear combination of a set of basis shapes, a novel view invariant human action recognition method is proposed based on non-rigid matrix factorization and Hidden Markov Models (HMMs). We show that the low dimensional weight coefficients of basis shapes by measurement matrix non-rigid factorization contain the key information for action recognition regardless of the viewpoint changing. Based on the extracted discriminative features, the HMMs is used for temporal dynamic modeling and robust action classification. The proposed method is tested using real life sequences and promising performance is achieved.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127211077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Robust Small-Object Detection for Outdoor Wide-Area Surveillance 面向室外广域监视的鲁棒小目标检测
IAPR International Workshop on Machine Vision Applications Pub Date : 2008-07-01 DOI: 10.1093/ietisy/e91-d.7.1922
Daisuke Abe, E. Segawa, Osafumi Nakayama, M. Shiohara, S. Sasaki, Nobuyuki Sugano, H. Kanno
{"title":"Robust Small-Object Detection for Outdoor Wide-Area Surveillance","authors":"Daisuke Abe, E. Segawa, Osafumi Nakayama, M. Shiohara, S. Sasaki, Nobuyuki Sugano, H. Kanno","doi":"10.1093/ietisy/e91-d.7.1922","DOIUrl":"https://doi.org/10.1093/ietisy/e91-d.7.1922","url":null,"abstract":"In this paper, we present a robust small-object detection method, which we call “Frequency Pattern Emphasis Subtraction (FPES)”, for wide-area surveillance such as that of harbors, rivers, and plant premises. For achieving robust detection under changes in environmental conditions, such as illuminance level, weather, and camera vibration, our method distinguishes target objects from background and noise based on the differences in frequency components between them. The evaluation results demonstrate that our method detected more than 95% of target objects in the images of large surveillance areas ranging from 30–75 meters at their center.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123305270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Motion Stabilization of Biped Robot by Gaze Control 基于注视控制的双足机器人运动稳定
IAPR International Workshop on Machine Vision Applications Pub Date : 2006-09-15 DOI: 10.7210/JRSJ.24.727
Shota Takizawa, S. Ushida, Takayuki Okatani, K. Deguchi
{"title":"Motion Stabilization of Biped Robot by Gaze Control","authors":"Shota Takizawa, S. Ushida, Takayuki Okatani, K. Deguchi","doi":"10.7210/JRSJ.24.727","DOIUrl":"https://doi.org/10.7210/JRSJ.24.727","url":null,"abstract":"We present a motion stabilization system for a biped robot that makes it possible to keep relative posture and position to a moving or stationary object. Our system consists of two layers of control subsystems, gaze control system and motion control system. In order to achieve an actual motion which follows exactly a scheduled one, the biped robot gazes a target to estimate errors of robot motion and adjusts both an actual motion and the scheduled one simultaneously. The gaze control system has 2 DOF controller, visual feedback part and feedforward part based on a scheduled robot motion. A periodic motion of robot body swing induced by walking allows us to estimate the distance to the target by forming a motion stereo. The scheduled motion is adjusted based on an adaptive law of Model Reference Adaptive Control (MRAC) .","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131239205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Robust Active Shape Model using AdaBoosted Histogram Classifiers 基于AdaBoosted直方图分类器的鲁棒主动形状模型
IAPR International Workshop on Machine Vision Applications Pub Date : 2006-07-01 DOI: 10.1093/ietisy/e89-d.7.2117
Yuanzhong Li, W. Ito
{"title":"Robust Active Shape Model using AdaBoosted Histogram Classifiers","authors":"Yuanzhong Li, W. Ito","doi":"10.1093/ietisy/e89-d.7.2117","DOIUrl":"https://doi.org/10.1093/ietisy/e89-d.7.2117","url":null,"abstract":"Active Shape Model (ASM) has been shown to be a powerful tool to aid the interpretation of images, espec ially in fac e alignment. ASM loc al appearanc e model parameter estimation is based on the assumption that residuals between model fit and data hav e a Gaussian distribution. Howev er, in fac e alignment, bec ause of c hanges in illumination, different fac ial ex pressions and obstac les lik e mustac hes and glasses, this assumption may be inac c urate. AdaBoost is widely used in fac e detec tion as a robust c lassific ation method, whic h does not need the Gaussian distribution assumption. I n this paper, we model loc al appearanc es by using AdaBoosted histogram c lassifiers to solv e the robustness problems, whic h hav e prev iously been enc ountered. Ex perimental results demonstrate the robustness of our method to align and loc ate fac ial features.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125248370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
GA-Based Affine PPM Using Matrix Polar Decomposition 基于矩阵极性分解的ga仿射PPM
IAPR International Workshop on Machine Vision Applications Pub Date : 2006-07-01 DOI: 10.1093/ietisy/e89-d.7.2053
M. Ezoji, K. Faez, H. Kanan, S. Mozaffari
{"title":"GA-Based Affine PPM Using Matrix Polar Decomposition","authors":"M. Ezoji, K. Faez, H. Kanan, S. Mozaffari","doi":"10.1093/ietisy/e89-d.7.2053","DOIUrl":"https://doi.org/10.1093/ietisy/e89-d.7.2053","url":null,"abstract":"Point pattern matching (PPM) arises in areas such as pattern recognition, digital video processing and computer vision. In this study, a novel Genetic Algorithm (GA) based method for matching affine-related point sets is described. Most common techniques for solving the PPM problem, consist in determining the correspondence between points localized spatially within two sets and then find the proper transformation parameters, using a set of equations. In this paper, we use this fact that the correspondence and transformation matrices are two unitary polar factors of Grammian matrices. We estimate one of these factors by the GA's population and then evaluate this estimation by computing an error function using another factor. This approach is an easily implemented one and because of using the GA in it, its computational complexity is lower than other known methods. Simulation results on synthetic and real point patterns with varying amount of noise, confirm that the algorithm is very effective.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117325242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Reliable and Robust Lane Detection System based on the Parallel Use of Three Algorithms for Driving Safety Assistance 一种基于三种算法并行应用的可靠鲁棒车道检测系统
IAPR International Workshop on Machine Vision Applications Pub Date : 2006-07-01 DOI: 10.1093/ietisy/e89-d.7.2092
R. Labayrade, J. Douret, J. Laneurit, R. Chapuis
{"title":"A Reliable and Robust Lane Detection System based on the Parallel Use of Three Algorithms for Driving Safety Assistance","authors":"R. Labayrade, J. Douret, J. Laneurit, R. Chapuis","doi":"10.1093/ietisy/e89-d.7.2092","DOIUrl":"https://doi.org/10.1093/ietisy/e89-d.7.2092","url":null,"abstract":"Road traffic incidents analysis has shown that a third of them occurs without any conflict which indicates problems with road following. In this paper a driving safety assistance system is introduced, whose aim is to prevent the driver drifting off or running off the road. The road following system is based on a frontal on-board monocular camera. In order to get a high degree of reliability and robustness, an original combination of three different algorithms is performed. Low level results from the first two algorithms are used to compute a reliability indicator and to update a high level model through the third algorithm using Kalman filtering. Searching areas of the road sides for the next image are also updated. Experimental results show the reliability and the robustness of this original association of three different algorithms. Various road situations are addressed, including roads with high curvature. A multi-lanes extension is also presented.","PeriodicalId":295384,"journal":{"name":"IAPR International Workshop on Machine Vision Applications","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123760420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 65
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