2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)最新文献_第3页

Is the transmission of depth data always necessary for 3D video streaming? 3D视频流是否总是需要传输深度数据?

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608123

Li Yu, M. Hannuksela, T. Tillo, Chunyu Lin, M. Gabbouj

引用次数: 0

Deep Dilated Convolutional Network for Material Recognition 材料识别的深度扩展卷积网络

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608160

Xiaoyue Jiang, Junna Du, B. Sun, Xiaoyi Feng

{"title":"Deep Dilated Convolutional Network for Material Recognition","authors":"Xiaoyue Jiang, Junna Du, B. Sun, Xiaoyi Feng","doi":"10.1109/IPTA.2018.8608160","DOIUrl":"https://doi.org/10.1109/IPTA.2018.8608160","url":null,"abstract":"Material is actually one of the intrinsic features for objects, consequently material recognition plays an important role in image understanding. For the same material, it may have various shapes and appearances, but keeps the same physical characteristic, which brings great challenges for material recognition. Most recent material recognition methods are based on image patches, and cannot give accurate segmentation results for each specific material. In this paper, we propose a deep learning based method to do pixel level material segmentation for whole images directly. In classical convolutional network, the spacial size of features becomes smaller and smaller with the increasing of convolutional layers, which loses the details for pixel-wise segmentation. Therefore we propose to use dilated convolutional layers to keep the details of features. In addition, the dilated convolutional features are combined with traditional convolutional features to remove the artifacts that are brough by dilated convolution. In the experiments, the proposed dilated network showed its effectiveness on the popular MINC dataset and its extended version.","PeriodicalId":272294,"journal":{"name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"110 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":"134577342","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

A Look At Non-Cooperative Presentation Attacks in Fingerprint Systems 指纹系统中的非合作表示攻击研究

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608133

Emanuela Marasco, S. Cando, Larry L Tang, Luca Ghiani, G. Marcialis

{"title":"A Look At Non-Cooperative Presentation Attacks in Fingerprint Systems","authors":"Emanuela Marasco, S. Cando, Larry L Tang, Luca Ghiani, G. Marcialis","doi":"10.1109/IPTA.2018.8608133","DOIUrl":"https://doi.org/10.1109/IPTA.2018.8608133","url":null,"abstract":"Scientific literature lacks of countermeasures specifically for fingerprint presentation attacks (PAs) realized with non-cooperative methods; even though, in realistic scenarios, it is unlikely that individuals would agree to duplicate their fingerprints. For example, replicas can be created from finger marks left on a surface without the person’s knowledge. Existing anti-spoofing mechanisms are trained to detect presentation attacks realized with cooperation of the user and are assumed to be able to identify non-cooperative spoofs as well. In this regard, latent prints are perceived to be of low quality and less likely to succeed in gaining unauthorized access. Thus, they are expected to be blocked without the need of a particular presentation attack detection system. Currently, the lowest Presentation Attack Detection (PAD) error rates on spoofs from latent prints are achieved using frameworks involving Convolutional Neural Networks (CNNs) trained on cooperative PAs; however, the computational requirement of these networks does not make them easily portable for mobile applications. Therefore, the focus of this paper is to investigate the degree of success of spoofs made from latent fingerprints to improve the understanding of their vitality features. Furthermore, we experimentally show the performance drop of existing liveness detectors when dealing with non-cooperative attacks and analyze the quality estimates pertaining to such spoofs, which are commonly believed to be of lower quality compared to the molds fabricated with user’s consensus.","PeriodicalId":272294,"journal":{"name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"33 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":"117109466","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

A Study of Measures for Contour-based Recognition and Localization of Known Objects in Digital Images 数字图像中基于轮廓的已知目标识别与定位方法研究

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608165

H. Abdulrahman, Baptiste Magnier

引用次数: 4

Human-Computer Interaction using Finger Signing Recognition with Hand Palm Centroid PSO Search and Skin-Color Classification and Segmentation 基于手掌质心粒子群搜索和肤色分类分割的手指签名识别人机交互

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608145

Z. Hamici

{"title":"Human-Computer Interaction using Finger Signing Recognition with Hand Palm Centroid PSO Search and Skin-Color Classification and Segmentation","authors":"Z. Hamici","doi":"10.1109/IPTA.2018.8608145","DOIUrl":"https://doi.org/10.1109/IPTA.2018.8608145","url":null,"abstract":"This paper presents a novel image processing technique for recognizing finger signs language alphabet. A human-computer interaction system is built based on the recognition of sign language which constitutes an interface between the computer and hearing-impaired persons, or as an assistive technology in industrial robotics. The sign language recognition is articulated on the extraction of the contours of the sign language alphabets, therefore, converting image recognition into one dimensional signal processing, which improves the recognition efficiency and significantly reduces the processing time. The pre-processing of images is performed by a novel skin-color region segmentation defined inside the standard RGB (sRGB) color space, then a morphological filtering is used for non-skin residuals removal. Afterwards, a circular correlation achieves the identification of the sign language after extracting the sign closed contour vector and performing matching between extracted vector and target alphabets vectors. The closed contour vector is generated around the hand palm centroid with position optimized by a particle swarm optimization algorithm search. Finally, a multi-objective function is used for computing the recognition score. The results presented in this paper for skin color segmentation, centroid search and pattern recognition show high effectiveness of the novel artificial vision engine.","PeriodicalId":272294,"journal":{"name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"1 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":"134638499","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

Acoustic Based Method for Automatic Segmentation of Images of Objects in Periodic Motion: detection of vocal folds edges case study 基于声学的周期性运动物体图像自动分割方法:声带边缘检测案例研究

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608152

Bartosz Kopczynski, P. Strumiłło, Marcin Just, E. Niebudek-Bogusz

{"title":"Acoustic Based Method for Automatic Segmentation of Images of Objects in Periodic Motion: detection of vocal folds edges case study","authors":"Bartosz Kopczynski, P. Strumiłło, Marcin Just, E. Niebudek-Bogusz","doi":"10.1109/IPTA.2018.8608152","DOIUrl":"https://doi.org/10.1109/IPTA.2018.8608152","url":null,"abstract":"We describe a novel image segmentation technique for automated detection of objects being in periodic motion that generates acoustic waves. The method is based on measuring similarity of two independently collected but time synchronized data, i.e. the audio signals and image sequences. Such a technique enables automatic and optimized segmentation procedure of a sequence of images depicting an oscillating object. The proposed segmentation procedure has been validated on the problem of detecting edges of vibrating vocal folds. The similarity measure of the synchronously collected sequence of laryngoscopic images and the voice signal is achieved by applying time-frequency analysis. The developed segmentation technique and motion analysis method can be applied for early detection of oscillation anomalies of the vocal folds which may cause hoarse voice, also known as dysphonia. In particular, the image segmentation result can aid the phoniatrist in the analysis of the vocal folds phonation process and help in early detection of voice anomalies.","PeriodicalId":272294,"journal":{"name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"17 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":"132377393","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

Pedestrian Detection in Infrared Images Using Fast RCNN 基于快速RCNN的红外图像行人检测

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608121

Asad Ullah, Hongmei Xie, M. Farooq, Zhaoyun Sun

引用次数: 25

Research on Low-Resolution Pedestrian Detection Algorithms based on R-CNN with Targeted Pooling and Proposal 基于目标池化的R-CNN低分辨率行人检测算法研究与建议

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608142

Peng Shi, Jun Wu, Kai Wang, Yao Zhang, Jiapei Wang, Juneho Yi

引用次数: 0

Classification of LiDAR Point Cloud based on Multiscale Features and PointNet 基于多尺度特征和点网的激光雷达点云分类

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608120

Zhao Zhongyang, Cheng Yinglei, Shi Xiaosong, Qin Xianxiang, Sun Li

引用次数: 1

Driver Drowsiness Detection in Facial Images 人脸图像中的驾驶员睡意检测

2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) Pub Date : 2018-11-01 DOI: 10.1109/IPTA.2018.8608130

F. Dornaika, J. Reta, Ignacio Arganda-Carreras, A. Moujahid

引用次数: 4