Proceedings 11th International Conference on Image Analysis and Processing最新文献_第10页

A local color descriptor for efficient scene-object recognition 一种用于高效场景物体识别的局部颜色描述符

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957049

E. Bigorgne, C. Achard, J. Devars

引用次数: 2

Integrated 2D and 3D images for face recognition 集成2D和3D图像，用于人脸识别

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.956984

Yingjie Wang, C. Chua, Yeong-Khing Ho, Ying Ren

{"title":"Integrated 2D and 3D images for face recognition","authors":"Yingjie Wang, C. Chua, Yeong-Khing Ho, Ying Ren","doi":"10.1109/ICIAP.2001.956984","DOIUrl":"https://doi.org/10.1109/ICIAP.2001.956984","url":null,"abstract":"This paper presents a feature-based face recognition system based on both 3D range data as well as 2D gray-level facial images. Ten 2D feature points and four 3D feature points are designed to be robust against changes of facial expressions and viewpoints and are described by Gabor filter responses in the 2D domain and point signature in the 3D domain. Localizing feature points in a new facial image is based on 3D-2D correspondence, average layout and corresponding bunch (covering a wide range of possible variations on each point). Extracted shape features from 3D feature points and texture features from 2D feature points are first projected into their own subspace using PCA. In subspace, the corresponding shape and texture weight vectors are then integrated to form an augmented vector which is used to represent each facial image. For a given test facial image, the best match in the model library is identified according to a classifier. Similarity function and support vector machine (SVM) are two types of classifier considered. Experimental results involving 2D persons with different facial expressions and extracted from different viewpoints have demonstrated the efficiency of our algorithm.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123394486","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: 18

Visual grouping and object recognition 视觉分组和对象识别

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957078

Jitendra Malik

{"title":"Visual grouping and object recognition","authors":"Jitendra Malik","doi":"10.1109/ICIAP.2001.957078","DOIUrl":"https://doi.org/10.1109/ICIAP.2001.957078","url":null,"abstract":"We develop a two-stage framework for parsing and understanding images, a process of image segmentation grouping pixels to form regions of coherent color and texture, and a process of recognition - comparing assemblies of such regions, hypothesized to correspond to a single object, with views of stored prototypes. We treat segmenting images into regions as an optimization problem: partition the image into regions such that there is high similarity within a region and low similarity across regions. This is formalized as the minimization of the normalized cut between regions. Using ideas from spectral graph theory, the minimization can be set as an eigenvalue problem. Visual attributes such as color, texture, contour and motion are encoded in this framework by suitable specification of graph edge weights. The recognition problem requires us to compare assemblies of image regions with previously stored proto-typical views of known objects. We have devised a novel algorithm for shape matching based on a relationship descriptor called the shape context. This enables us to compute similarity measures between shapes which, together with similarity measures for texture and color, can be used for object recognition. The shape matching algorithm has yielded excellent results on a variety of different 2D and 3D recognition problems.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258081","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: 8

Noise filtering of periodic image sequences 周期性图像序列的噪声滤波

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957004

A. Plebe

引用次数: 1

A neural network-based image processing system for detection of vandal acts in unmanned railway environments 一种基于神经网络的图像处理系统，用于无人驾驶铁路环境中的破坏行为检测

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957064

C. Sacchi, C. Regazzoni, G. Vernazza

引用次数: 27

Improved minimum distance classification with Gaussian outlier detection for industrial inspection 基于高斯离群点检测的工业检测改进最小距离分类

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957073

D. Toth, T. Aach

{"title":"Improved minimum distance classification with Gaussian outlier detection for industrial inspection","authors":"D. Toth, T. Aach","doi":"10.1109/ICIAP.2001.957073","DOIUrl":"https://doi.org/10.1109/ICIAP.2001.957073","url":null,"abstract":"A pattern recognition system used for industrial inspection has to be highly reliable and fast. The reliability is essential for reducing the cost caused by incorrect decisions, while speed is necessary for real-time operation. We address the problem of inspecting optical media like compact disks and digital versatile disks. As the disks are checked during production and the output of the production line has to be sufficiently high, the time available for the whole examination is very short, ie, about 1 sec per disk. In such real-time applications, the well-known minimum distance algorithm is often used as classifier. However, its main drawback is the unreliability when the training data are not well clustered in feature-space. Here we describe a method for off-line outlier detection, which cleans the training data set and yields substantially better classification results. It works on a statistical test basis. In addition, two improved versions of the minimum distance classifier, which both yield higher rates of correct classification with practically no speed-loss are presented. To evaluate the results, we compare them to the results obtained using a standard minimum distance classifier, a k-nearest neighbor classifier, and a fuzzy k-nearest neighbor classifier.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123330493","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: 18

A hierarchical framework for modal correspondence matching 模态对应匹配的层次框架

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957030

Marco Carcassoni, E. Hancock

{"title":"A hierarchical framework for modal correspondence matching","authors":"Marco Carcassoni, E. Hancock","doi":"10.1109/ICIAP.2001.957030","DOIUrl":"https://doi.org/10.1109/ICIAP.2001.957030","url":null,"abstract":"The modal correspondence method of L.S. Shapiro and J.M. Brady (see Image and Vision Computing, vol.10, p.283-8, 1992) aims to match point-sets by comparing the eigenvectors of a pairwise point proximity matrix. Although elegant by means of its matrix representation, the method is notoriously susceptible to differences in the relational structure of the point-sets under consideration. We demonstrate how the method can be rendered robust to structural differences by adopting a hierarchical approach. We place the modal matching problem in a probabilistic setting in which the arrangement of pairwise clusters can be used to constrain the individual point correspondences. We commence by using an iterative pairwise clustering method which can be applied to locate the main structure in the point-sets under study. Once we have located point clusters, we compute within-cluster and between-cluster proximity matrices. The modal coefficients for these two sets of proximity matrices are used to compute the probabilities that the detected cluster-centres are in correspondence and also the probabilities that individual points are in correspondence. We develop an evidence-combining framework which draws on these two sets of probabilities to locate point correspondences. In this way, the arrangement of the cluster-centre correspondences constrain the individual point correspondences.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123344154","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: 0

Effective moving cast shadow detection for monocular color image sequences 单眼彩色图像序列的有效运动投影检测

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 2001-09-26 DOI: 10.1109/ICIAP.2001.957043

Gsk Fung, N. Yung, G. Pang, A. Lai

{"title":"Effective moving cast shadow detection for monocular color image sequences","authors":"Gsk Fung, N. Yung, G. Pang, A. Lai","doi":"10.1109/ICIAP.2001.957043","DOIUrl":"https://doi.org/10.1109/ICIAP.2001.957043","url":null,"abstract":"For an accurate scene analysis in monocular image sequences, a robust segmentation of a moving object from the static background is generally required. However, the existence of moving cast shadow may lead to an inaccurate object segmentation, and as a result, lead to further erroneous scene analysis. An effective detection of moving cast shadow in monocular color image sequences is developed. Firstly, by realizing the various characteristics of shadow in luminance, chrominance, and gradient density, an indicator, called shadow confidence score, of the probability of the region classified as cast shadow is calculated. Secondly the canny edge detector is employed to detect edge pixels in the detected region. These pixels are then bounded by their convex hull, which estimates the position of the object. Lastly, by analyzing the shadow confidence score and the bounding hull, the cast shadow is identified as those regions outside the bounding hull and with high shadow confidence score. A number of typical outdoor scenes are evaluated and it is shown that our method can effectively detect the associated cast shadow from the object of interest.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115539143","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: 40

Attentive billboards 细心的广告牌

Proceedings 11th International Conference on Image Analysis and Processing Pub Date : 1900-01-01 DOI: 10.1109/ICIAP.2001.957002

I. Haritaoglu, M. Flickner

引用次数: 13