发布求助
文献互助 智能选刊 最新文献

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)最新文献

筛选
英文 中文
Modeling of 2D Objects with Weighted-Quadratic Trigonometric Spline 二维物体的加权二次三角样条建模
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.15
M. Sarfraz, Shamaila Samreen, M. Hussain
{"title":"Modeling of 2D Objects with Weighted-Quadratic Trigonometric Spline","authors":"M. Sarfraz, Shamaila Samreen, M. Hussain","doi":"10.1109/CGIV.2016.15","DOIUrl":"https://doi.org/10.1109/CGIV.2016.15","url":null,"abstract":"An imperative scheme is adopted to model 2D objects by constructing a weighted-spline using a quadratic trigonometric function with well controlled shape influences of parameters. The curve models, constructed through the suggested scheme, own the best possible geometric properties such as convex hull, partition of unity, affine invariance and variation diminishing. The illustration of the method is supportive for various shape effects using interval tension property. The proposed C1 spline method is modest overall.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114851760","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
Abnormal Events Detection Based on Trajectory Clustering 基于轨迹聚类的异常事件检测
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.65
Najla Bouarada Ghrab, Emna Fendri, Mohamed Hammami
{"title":"Abnormal Events Detection Based on Trajectory Clustering","authors":"Najla Bouarada Ghrab, Emna Fendri, Mohamed Hammami","doi":"10.1109/CGIV.2016.65","DOIUrl":"https://doi.org/10.1109/CGIV.2016.65","url":null,"abstract":"Trajectories of moving objects provide crucial clues for video event analysis especially in surveillance applications. In this paper, we proposed a novel approach for detecting abnormal events in video surveillance. Our approach is based on trajectory analysis involving two phases. In the first phase, we extracted clusters of normal events through an agglomerative hierarchical clustering of saved trajectories that were of different lengths, of different local time shifts and containing noise. Then, for each cluster a model was established. In the second phase, we aimed to classify a new event as normal or abnormal one. To achieve this objective, a comparison was performed with the extracted clusters' models thereby reducing the complexity and accelerating the classification process. Experiments were conducted to demonstrate the efficacy and the performance of our approach.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131051803","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
Grouping K-Means Adjacent Regions for Semantic Image Annotation Using Bayesian Networks 基于贝叶斯网络的k -均值分组相邻区域语义图像标注
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.54
M. Oujaoura, R. El Ayachi, B. Minaoui, M. Fakir, O. Bencharef
{"title":"Grouping K-Means Adjacent Regions for Semantic Image Annotation Using Bayesian Networks","authors":"M. Oujaoura, R. El Ayachi, B. Minaoui, M. Fakir, O. Bencharef","doi":"10.1109/CGIV.2016.54","DOIUrl":"https://doi.org/10.1109/CGIV.2016.54","url":null,"abstract":"To perform a semantic search on a large dataset of images, we need to be able to transform the visual content of images (colors, textures, shapes) into semantic information. This transformation, called image annotation, assigns a caption or keywords to the visual content in a digital image. In this paper we try to resolve partially the region homogeneity problem in image annotation, we propose an approach to annotate image based on grouping adjacent regions, we use the k-means algorithm as the segmentation algorithm while the texture and GIST descriptors are used as features to represent image content. The Bayesian networks were been used as classifiers in order to find and allocate the appropriate keywords to this content. The experimental results were been obtained from the ETH-80 image database.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128895551","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: 2
Automatic Bifurcation Detection in Coronary X-Ray Angiographies 冠状动脉x线造影中的自动分岔检测
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.70
Asma Kerkeni, A. Ben Abdallah, A. Manzanera, M. H. Bedoui
{"title":"Automatic Bifurcation Detection in Coronary X-Ray Angiographies","authors":"Asma Kerkeni, A. Ben Abdallah, A. Manzanera, M. H. Bedoui","doi":"10.1109/CGIV.2016.70","DOIUrl":"https://doi.org/10.1109/CGIV.2016.70","url":null,"abstract":"The detection of vascular bifurcation in X-ray images is important for several medical applications. They are used as landmarks for image registration, vessel segmentation and tracking. Although many bifurcation extraction methods have been proposed in recent years, very few work deals with coronary bifurcation in X-ray images. In this paper, we present a new bifurcation detector based on the multiscale Hessian analysis. It can be seen as a scale specific Histogram of Eigenvectors weighted by the vesselness measure. Pixels with three peaks in their immediate neighbourhood are considered as bifurcation candidates. Based on this detector, a novel bifurcationness measure is proposed. The method is tested on real coronary artery angiographies and shows better results compared to other bifurcation detectors.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115044197","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
On Performance Evaluation of Registration Algorithms for 3D Point Clouds 三维点云配准算法的性能评价
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.18
Mouna Attia, Y. Slama, M. Kamoun
{"title":"On Performance Evaluation of Registration Algorithms for 3D Point Clouds","authors":"Mouna Attia, Y. Slama, M. Kamoun","doi":"10.1109/CGIV.2016.18","DOIUrl":"https://doi.org/10.1109/CGIV.2016.18","url":null,"abstract":"3D point Geometric alignment is a challenging task encountered in many scientific applications related to different fields such as robotics and computer vision. For this reason, the well-known 3D registration problem has been extensively studied, and a lot of efficient 3D registration algorithms (RA) exist. Even though many surveys in the literature addressed RA's, none to our knowledge is especially interested in their use in robotic fields and more precisely in dimensional control of mechanical pieces. Our present work involving both a theoretical and an experimental study compares some local and non-rigid RAs, used to align large point clouds representing mechanical pieces. This paper is two-fold and permits first to uncover the similarities and differences between four known RAs which are ICP, NDT, Softassign and RANSAC and then to establish an inter RAs comparative performance evaluation based on accuracy, speed and other new specific metrics we have defined.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133727075","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: 16
Classification and Recognition of Dental Images Using a Decisional Tree 基于决策树的牙齿图像分类与识别
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.82
Hicham Riri, A. Elmoutaouakkil, A. Beni-Hssane, Farid Bourezgui
{"title":"Classification and Recognition of Dental Images Using a Decisional Tree","authors":"Hicham Riri, A. Elmoutaouakkil, A. Beni-Hssane, Farid Bourezgui","doi":"10.1109/CGIV.2016.82","DOIUrl":"https://doi.org/10.1109/CGIV.2016.82","url":null,"abstract":"Recognition and classification of images have a wide field of applications, especially in medical images. In order to provide orthodontists a solution for classification of patients' images to evaluate the evolution of their treatment, we need to use latest efficient technics of classification. In this paper, we propose an algorithm based on a decisional tree to classify and recognize 19 types of dental images. This hierarchical representation can be interpreted as a set of hierarchical types stored in leafs tree structure. By using several extracted features from color images acquired with a digital camera and grayscale images acquired by x-ray scanner. Such as facial features and skin color using YCbCr color-space. The proposed technique has been evaluated on a large data set of four main types namely: mold, intra-oral, extra-oral and radiographic images of different patients. Hence, experimental results demonstrate the good performances of this approach.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132667575","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
Markovian Segmentation of Color and Gray Level Images 彩色和灰度图像的马尔可夫分割
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.57
M. Ameur, N. Idrissi, C. Daoui
{"title":"Markovian Segmentation of Color and Gray Level Images","authors":"M. Ameur, N. Idrissi, C. Daoui","doi":"10.1109/CGIV.2016.57","DOIUrl":"https://doi.org/10.1109/CGIV.2016.57","url":null,"abstract":"The image segmentation is a fundamental tool to analyze and detect objects of interest that can be applied in many fields (medicine, satellite). In this work, we present a classical Markov model for unsupervised image segmentation: \"Hidden Markov Chain with Independent Noise\" (HMC-IN) for segmenting both gray and color images. Then, we compare five iterative algorithms EM, GEM, SEM, MCEM and ICE for estimating parameters of this model under two final bayesian decision criteria MAP and MPM according to the execution time, the convergence, the PNSR index and the rate error.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"12 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125641210","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: 4
An Effective Soft Multiple-Assignments Strategies for Enhancing the Accuracy of the Content-Based Image Retrieval Systems 提高基于内容的图像检索系统精度的一种有效的软多重赋值策略
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.47
Zied Elleuch, K. Marzouki
{"title":"An Effective Soft Multiple-Assignments Strategies for Enhancing the Accuracy of the Content-Based Image Retrieval Systems","authors":"Zied Elleuch, K. Marzouki","doi":"10.1109/CGIV.2016.47","DOIUrl":"https://doi.org/10.1109/CGIV.2016.47","url":null,"abstract":"The multiple-assignments approach alleviates the quantization error and enhances the accuracy of the Content-Based Image Retrieval (CBIR) systems. It aims to hard assign each feature vector to k-nearest visual words. However, during the matching step, the k-nearest visual words are used independently and ignore the significant of the best visual word. In this paper, we present our CBIR system which encapsulates several approaches such Hamming embedding, soft-assignment, multiple-assignments and graph fusion. We particularly focus on the multiple-assignments strategy. We propose an efficient soft multiple-assignments strategy to highlight the best k-nearest visual word. To this end, we explore the SOM topology which proved its performance in so doing. Moreover, we use graph fusion approach to fuse multi-features ranking lists. Extensive experiments are conducted on Holiday and Ukbench public datasets. The experimental results are promising and outperform the state-of-the-art CBIR systems. In fact, we have reached a mAP = 85.6 on Holidays dataset and a KS score of 3.87 on Ukbench dataset.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121682858","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
Facial Expression Recognition Using Decision Trees 基于决策树的面部表情识别
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.33
Fatima Zahra Salmam, Abdellah Madani, M. Kissi
{"title":"Facial Expression Recognition Using Decision Trees","authors":"Fatima Zahra Salmam, Abdellah Madani, M. Kissi","doi":"10.1109/CGIV.2016.33","DOIUrl":"https://doi.org/10.1109/CGIV.2016.33","url":null,"abstract":"Emotion recognition from facial expressions is generally performed in three steps: face detection, features extraction and classification of expressions. The present work focuses on two points: Firstly, a new extraction method is presented based on the geometric approach. This method consists of calculating six distances in order to measure parts of the face that better describe a facial expression. Secondly, an automatic supervised learning method called decision tree is applied on two databases (JAFEE and COHEN), in order to have a facial expressions classifying system with seven possible classes (six basic emotions plus neutral), this system uses as input the six distances previously calculated (using Euclidian, Manhattan or Minkowski distance) for each face. Our results achieved a recognition rate of 89.20% and 90.61% respectively in JAFFE and COHEN database.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123804768","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: 51
Phase Extraction Method in Fringe Projection Profilometry Using Instantaneous Frequency 基于瞬时频率的条纹投影轮廓术中的相位提取方法
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.21
Rachid Idrissi El-Azami, H. Tairi, B. Bellach
{"title":"Phase Extraction Method in Fringe Projection Profilometry Using Instantaneous Frequency","authors":"Rachid Idrissi El-Azami, H. Tairi, B. Bellach","doi":"10.1109/CGIV.2016.21","DOIUrl":"https://doi.org/10.1109/CGIV.2016.21","url":null,"abstract":"Three-dimensional (3-D) surface profiles can be obtained by using non-contact optical profilometry techniques. Fringe projection profilometry is widely used for three dimensional (3-D) surface shape, measurement using phase-shifting (PS) methods with multiple projected fringe pattern or transform methods with single projected fringe pattern. In this paper, Our research has focused on the study of the phase extraction method from a single fringe pattern in fringe projection profilometry using the instantaneous frequency method as one of the relevant techniques in the field of signal processing. The main advantage of this method of analysis based on the notion of instantaneous frequency is that it requires only one fringe pattern, which made from this method well suited for real-time measurement. The effectiveness of the instantaneous frequency method is illustrated by their comparison with traditional methods.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122574002","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信