2018 7th European Workshop on Visual Information Processing (EUVIP)最新文献_第3页

Compound Markov Random Field Model of Signals on Graph: An Application to Graph Learning 图上信号的复合马尔可夫随机场模型:在图学习中的应用

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611758

S. Colonnese, Giulio Pagliari, M. Biagi, R. Cusani

{"title":"Compound Markov Random Field Model of Signals on Graph: An Application to Graph Learning","authors":"S. Colonnese, Giulio Pagliari, M. Biagi, R. Cusani","doi":"10.1109/EUVIP.2018.8611758","DOIUrl":"https://doi.org/10.1109/EUVIP.2018.8611758","url":null,"abstract":"In this work we address the problem of Signal on Graph (SoG) modeling, which can provide a powerful image processing tool for suitable SoG construction. We propose a novel SoG Markovian model suited to jointly characterizing the graph signal values and the graph edge processes. Specifically, we resort to the compound MRF called pixel-edge model formerly introduced in natural images modeling and we reformulate it to frame SoG modeling. We derive the Maximum A Posteriori Laplacian estimator associated to the compound MRF, and we show that it encompasses simpler state-of-the-art estimators for proper parameter settings. Numerical simulations show that the Maximum A Priori Laplacian estimator based on the proposed model outperforms state-of-the-art competitors under different respects. The Spectral Graph Wavelet Transform basis associated to the Maximum A Priori Laplacian estimation guarantees excellent compression of the given SoG. These results show that the compound MRF represents a powerful theoretical tool to characterize the strong and rich interactions that can be found between the signal values and the graph structures, and pave the way to its application to various SoG problems.","PeriodicalId":252212,"journal":{"name":"2018 7th European Workshop on Visual Information Processing (EUVIP)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126285659","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

A Neural Network-based Approach for Public Transportation Prediction with Traffic Density Matrix 基于神经网络的交通密度矩阵公共交通预测方法

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611683

Dancho Panovski, Veronica Scurtu, T. Zaharia

引用次数: 5

Proceedings of the 2018 7th European Workshop on Visual Information Processing (EUVIP) 2018第七届欧洲视觉信息处理研讨会论文集

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/euvip.2018.8611752

引用次数: 0

A Novel Human Identification Method by Gait using Dynamics of Feature Points and Local Shape Features 基于特征点动力学和局部形状特征的步态识别方法

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611680

Daisuke Imoto, K. Kurosawa, K. Tsuchiya, K. Kuroki, Manato Hirabayashi, N. Akiba, H. Kakuda, K. Tanabe, Yoshinori Hawai

{"title":"A Novel Human Identification Method by Gait using Dynamics of Feature Points and Local Shape Features","authors":"Daisuke Imoto, K. Kurosawa, K. Tsuchiya, K. Kuroki, Manato Hirabayashi, N. Akiba, H. Kakuda, K. Tanabe, Yoshinori Hawai","doi":"10.1109/EUVIP.2018.8611680","DOIUrl":"https://doi.org/10.1109/EUVIP.2018.8611680","url":null,"abstract":"Gait analysis has been recently evolving techniques by which we can identify individuals using their gait patterns. One of appearance-based methods based on GEI (Gait Energy Image) has been used for forensic purpose in Japan. As long as the condition of two footages is close to an ideal case, which means the two footages are the same view-angle, clothing, resolution, frame-rate and stable walking, this method has been very useful so far. However, if the condition becomes far from an ideal case, the identification accuracy has become dropped down, resulting in analysis impossible. Here, we construct a novel human identification method based on comparison of dynamic features, which takes advantage of features of both appearance-based method and model-based method. Feature points (resemble to joint-points in model-based method) and those local shape features are semi-automatically extracted from silhouette sequences, and then the matching probability of two footages is calculated by comparing the dynamics of extracted features. It is found that GEI-based method is more useful in cases of frontal view, low resolution and comparison of multi view-angles, whereas the proposed method is more useful in cases of lateral view, low frame-rate and clothing variation condition. The results suggested that GEI-based method is superior to characterizing ‘figure’ information, whereas the proposed method is superior to characterizing ‘dynamic’ information of human gait.","PeriodicalId":252212,"journal":{"name":"2018 7th European Workshop on Visual Information Processing (EUVIP)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122779034","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

Choice of the Parameter for BM3D Denoising Algorithm Using No- Reference Metric 无参考度量BM3D去噪算法参数的选择

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611679

N. Mamaev, D. Yurin, A. Krylov

引用次数: 8

DCT-Tensor-Net for Solar Flares Detection on IRIS Data 基于IRIS数据的dct -张量网太阳耀斑探测

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611672

Denis Ullmann, S. Voloshynovskiy, L. Kleint, S. Krucker, M. Melchior, C. Huwyler, Brandon Panos

引用次数: 0

Grid Warping Postprocessing for Linear Motion Blur in Images 网格翘曲后处理的线性运动模糊图像

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611700

A. Nasonov, Yakov Pchelintsev, A. Krylov

引用次数: 1

A Hybrid Approach to Hand Detection and Type Classification in Upper-Body Videos 上半身视频中手部检测与类型分类的混合方法

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611755

Katerina Papadimitriou, G. Potamianos

{"title":"A Hybrid Approach to Hand Detection and Type Classification in Upper-Body Videos","authors":"Katerina Papadimitriou, G. Potamianos","doi":"10.1109/EUVIP.2018.8611755","DOIUrl":"https://doi.org/10.1109/EUVIP.2018.8611755","url":null,"abstract":"Detection of hands in videos and their classification into left and right types are crucial in various human-computer interaction and data mining systems. A variety of effective deep learning methods have been proposed for this task, such as region-based convolutional neural networks (R-CNNs), however the large number of their proposal windows per frame deem them computationally intensive. For this purpose we propose a hybrid approach that is based on substituting the “selective search” R-CNN module by an image processing pipeline assuming visibility of the facial region, as for example in signing and cued speech videos. Our system comprises two main phases: preprocessing and classification. In the preprocessing stage we incorporate facial information, obtained by an AdaBoost face detector, into a skin-tone based segmentation scheme that drives Kalman filtering based hand tracking, generating very few candidate windows. During classification, the extracted proposal regions are fed to a CNN for hand detection and type classification. Evaluation of the proposed hybrid approach on four well-known datasets of gestures and signing demonstrates its superior accuracy and computational efficiency over the R-CNN and its variants.","PeriodicalId":252212,"journal":{"name":"2018 7th European Workshop on Visual Information Processing (EUVIP)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132331745","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

Using Visible+NIR information for CNN face recognition 利用可见光+近红外信息进行CNN人脸识别

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611681

Sanae Boutarfass, B. Besserer

引用次数: 2

On the Layer Selection in Small-Scale Deep Networks 小尺度深度网络中的层选择

2018 7th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2018-11-01 DOI: 10.1109/EUVIP.2018.8611738

A. Muravev, Jenni Raitoharju, M. Gabbouj

引用次数: 2