2018 Digital Image Computing: Techniques and Applications (DICTA)最新文献_第4页

Human Brain Tissue Segmentation in fMRI using Deep Long-Term Recurrent Convolutional Network 基于深度长期递归卷积网络的fMRI人脑组织分割

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615850

Sui Paul Ang, S. L. Phung, M. Schira, A. Bouzerdoum, S. T. Duong

引用次数: 8

Online Relational Manifold Learning for Multiview Segmentation in Echocardiography 超声心动图多视点分割的在线关系流形学习

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615773

G. Belous, Andrew Busch, D. Rowlands, Yongsheng Gao

{"title":"Online Relational Manifold Learning for Multiview Segmentation in Echocardiography","authors":"G. Belous, Andrew Busch, D. Rowlands, Yongsheng Gao","doi":"10.1109/DICTA.2018.8615773","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615773","url":null,"abstract":"Accurate delineation of the left ventricle (LV) endocardial border in echocardiography is of vital importance for the diagnosis and treatment of heart disease. Effective segmentation of the LV is challenging due to low contrast, signal dropout and acoustic noise. In the situation where low level and region-based image cues are unable to define the LV boundary, shape prior models are critical to infer shape. These models perform well when there is low variability in the underlying shape subspace and the shape instance produced by appearance cues does not contain gross errors, however in the absence of these conditions results are often much poorer. In this paper, we first propose a shape model to overcome the problem of modelling complex shape subspaces. Our method connects the implicit relationship between image features and shape by extending graph regularized sparse nonnegative matrix factorization (NMF) to jointly learn the structure and connection between two low dimensional manifolds comprising image features and shapes, respectively. We extend conventional NMF learning to an online learning-based approach where the input image is used to leverage the learning and connection of each manifold to the most relevant subspace regions. This ensures robust shape inference and a shape model constructed from contextually relevant shapes. A fully automatic segmentation approach using a probabilistic framework is then proposed to detect the LV endocardial border. Our method is applied to a diverse dataset that contains multiple views of the LV. Results show the effectiveness of our approach compared to state-of-the-art methods.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128932684","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

DICTA 2018 Conference Sponsors 2018年DICTA会议赞助商

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/dicta.2018.8615752

引用次数: 0

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615804

Di Wu, N. Sharma, M. Blumenstein

{"title":"Similar Gesture Recognition using Hierarchical Classification Approach in RGB Videos","authors":"Di Wu, N. Sharma, M. Blumenstein","doi":"10.1109/DICTA.2018.8615804","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615804","url":null,"abstract":"Recognizing human actions from the video streams has become one of the very popular research areas in computer vision and deep learning in the recent years. Action recognition is wildly used in different scenarios in real life, such as surveillance, robotics, healthcare, video indexing and human-computer interaction. The challenges and complexity involved in developing a video-based human action recognition system are manifold. In particular, recognizing actions with similar gestures and describing complex actions is a very challenging problem. To address these issues, we study the problem of classifying human actions using Convolutional Neural Networks (CNN) and develop a hierarchical 3DCNN architecture for similar gesture recognition. The proposed model firstly combines similar gesture pairs into one class, and classify them along with all other class, as a stage-1 classification. In stage-2, similar gesture pairs are classified individually, which reduces the problem to binary classification. We apply and evaluate the developed models to recognize the similar human actions on the HMDB51 dataset. The result shows that the proposed model can achieve high performance in comparison to the state-of-the-art methods.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131556502","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

Heuristic Evaluations of Cultural Heritage Websites 文化遗产网站的启发式评价

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615847

Duyen Lam, Atul Sajjanhar

引用次数: 3

Clearing Multiview Structure Graph from Inconsistencies 清除多视图结构图的不一致性

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615787

S. Kabbour, Pierre-Yves Richard

引用次数: 0

Image Representation using Bag of Perceptual Curve Features 使用感知曲线特征包的图像表示

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615816

Elham Etemad, Q. Gao

引用次数: 0

Image Processing for Traceability: A System Prototype for the Southern Rock Lobster (SRL) Supply Chain 可追溯性的图像处理:南方岩龙虾(SRL)供应链的系统原型

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615842

Son Anh Vo, J. Scanlan, L. Mirowski, P. Turner

{"title":"Image Processing for Traceability: A System Prototype for the Southern Rock Lobster (SRL) Supply Chain","authors":"Son Anh Vo, J. Scanlan, L. Mirowski, P. Turner","doi":"10.1109/DICTA.2018.8615842","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615842","url":null,"abstract":"This paper describes how conventional image processing techniques can be applied to the grading of Southern Rock Lobsters (SRL) to produce a high quality data layer which could be an input into product traceability. The research is part of a broader investigation into designing a low-cost biometric identification solution for use along the entire lobster supply chain. In approaching the image processing for lobster grading a key consideration is to develop a system capable of using low cost consumer grade cameras readily available in mobile phones. The results confirm that by combining a number of common techniques in computer vision it is possible to capture and process a set of valuable attributes from sampled lobster image including color, length, weight, legs and sex. By combining this image profile with other pre-existing data on catch location and landing port each lobster can be verifiably tracked along the supply chain journey to markets in China. The image processing research results achieved in the laboratory show high accuracy in measuring lobster carapace length that is vital for weight conversion calculations. The results also demonstrate the capability to obtain reliable values for average color, tail shape and number of legs on a lobster used in grading classifications. The findings are a major first step in the development of individual lobster biometric identification and will directly contribute to automating lobster grading in this valuable Australian fishery.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117154461","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 New Method for Removing Asymmetric High Density Salt and Pepper Noise

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615814

Allan Pennings, I. Svalbe

引用次数: 0

Drivers Performance Evaluation using Physiological Measurement in a Driving Simulator 驾驶模拟器中基于生理测量的驾驶员性能评价

2018 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/DICTA.2018.8615763

Afsaneh Koohestani, P. Kebria, A. Khosravi, S. Nahavandi

{"title":"Drivers Performance Evaluation using Physiological Measurement in a Driving Simulator","authors":"Afsaneh Koohestani, P. Kebria, A. Khosravi, S. Nahavandi","doi":"10.1109/DICTA.2018.8615763","DOIUrl":"https://doi.org/10.1109/DICTA.2018.8615763","url":null,"abstract":"Monitoring the drivers behaviour and detecting their awareness are of vital importance for road safety. Drivers distraction and low awareness are already known to be the main reason for accidents in the world. Distraction-related crashes have greatly increased in recent years due to the proliferation of communication, entertainment, and malfunctioning of driver assistance systems. Accordingly, there is a need for advanced systems to monitor the drivers behaviour and generate a warning if a degradation in a drivers performance is detected. The purpose of this study is to analyse the vehicle and drivers data to detect the onset of distraction. Physiological measurements, such as palm electrodermal activity, heart rate, breathing rate, and perinasal perspiration are analysed and applied for the development of the monitoring system. The dataset used in this research has these measurements for 68 healthy participants (35 male, 33 female/17 elderly, 51 young). These participants completed two driving sessions in a driving simulator, including the normal and loaded drive. In the loaded scenario, drivers were texting back words. The lane deviation of vehicle was recorded as the response variable. Different classification algorithms such as generalised linear, support vector model, K-nearest neighbour and random forest machines are implemented to classify the driver's performance based on input features. Prediction results indicate that random forest performs the best by achieving an area under the curve (AUC) of over 91%. It is also found that biographic features are not informative enough to analyse drivers performance while perinasal perspiration carries the most information.","PeriodicalId":130057,"journal":{"name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123474926","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