2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)最新文献

Machine Learning Based Detection of Hearing Loss Using Auditory Perception Responses 基于听觉感知反应的机器学习听力损失检测

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00034

Muhammad Ilyas, A. Naït-Ali

引用次数: 3

Perceived Effects of Static and Dynamic Sparkle in Captured Effect Coatings 俘获效应涂层中静态和动态闪光的感知效应

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00119

J. Filip, M. Kolafová, R. Vávra

引用次数: 1

A Gaussian Recursive Filter Parallel Implementation with Overlapping 一种具有重叠的高斯递归滤波器并行实现

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00105

P. D. Luca, A. Galletti, L. Marcellino

{"title":"A Gaussian Recursive Filter Parallel Implementation with Overlapping","authors":"P. D. Luca, A. Galletti, L. Marcellino","doi":"10.1109/SITIS.2019.00105","DOIUrl":"https://doi.org/10.1109/SITIS.2019.00105","url":null,"abstract":"Gaussian convolutions computation is required in several scientific fields and, to this aim, efficient approximation methods, based on Recursive Filters (RFs), have been developed recently. Among them, Gaussian Recursive Filters (RFs) are designed to approximate the Gaussian convolution in a very efficient way. The accuracy of these methods, as is well known, can be improved by means of the use of the so-called K-iterated Gaussian recursive filters, that is in the repeated application of the basic RF. To improve the provided accuracy, K-iterated versions of these methods are also considered. Since it is often necessary to handle large size one-dimensional input signals, a parallel approach becomes mandatory. Recently, we proposed a parallel algorithm for the implementation of the K-iterated first-order Gaussian RF on multicore architectures. Here, using a similar parallelization strategy, based on a domain decomposition with overlapping, we propose a new implementation that would exploit, in terms of both accuracy and performance, the GPU (Graphics Processing Unit) capabilities on CUDA environment. Tests and experiments confirm the reliability and the efficiency of the proposed implementation.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"55 21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115351211","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

Low-Light Image Enhancement via Adaptive Shape and Texture Prior 通过自适应形状和纹理先验的弱光图像增强

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00024

Kazuki Kurihara, Hiromi Yoshida, Y. Iiguni

{"title":"Low-Light Image Enhancement via Adaptive Shape and Texture Prior","authors":"Kazuki Kurihara, Hiromi Yoshida, Y. Iiguni","doi":"10.1109/SITIS.2019.00024","DOIUrl":"https://doi.org/10.1109/SITIS.2019.00024","url":null,"abstract":"Low light images affect various computer vision algorithms due to their low visibility and much noise hidden in dark regions. Although many methods based on the Retinex theory, which decomposes an observed image into the reflectance and illumination, have been proposed to alleviate the problem, existing methods inevitably cause under-and over-enhancement. In this paper, we propose a new joint optimization equation that sufficiently considers the features of both reflectance and illumination. More concretely, we adopt L2-Lp norm regularization terms to estimate the reflectance as much as possible to preserve details and textures, and the illumination as much as possible to preserve the structure information with texture-less. We solve the optimization equation in an alternating minimization method. Furthermore, we introduce a new adaptive texture prior to reveal more details and textures with noise reduction on both bright and dark regions. Experimental results, including qualitative and quantitative evaluations, show that the proposed method can establish a better performance than the other state-of-the-art methods.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122459919","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

Time Unification on Local Binary Patterns Three Orthogonal Planes for Facial Expression Recognition 局部二值模式三正交平面的时间统一面部表情识别

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00076

Reda Belaiche, C. Migniot, D. Ginhac, Fan Yang

{"title":"Time Unification on Local Binary Patterns Three Orthogonal Planes for Facial Expression Recognition","authors":"Reda Belaiche, C. Migniot, D. Ginhac, Fan Yang","doi":"10.1109/SITIS.2019.00076","DOIUrl":"https://doi.org/10.1109/SITIS.2019.00076","url":null,"abstract":"Machine learning has known a tremendous growth within the last years, and lately, thanks to that, some computer vision algorithms started to access what is difficult or even impossible to perceive by the human eye. While deep learning based computer vision algorithms have made themselves more and more present in the recent years, more classical feature extraction methods, such as the ones based on Local Binary Patterns (LBP), still present a non negligible interest, especially when dealing with small datasets. Furthermore, this operator has proven to be quite useful for facial emotions and human gestures recognition in general. Micro-Expression (ME) classification is among the applications of computer vision that heavily relied on hand crafted features in the past years. LBP Three Orthogonal Planes (LBP_TOP) is one of the most used hand crafted features extractor in the scientific literature to tackle the problem of ME classification. In this paper we present a time unification method that provides better results than the classical LBP_TOP while also drastically reducing the calculations required for feature extraction.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121674082","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

Benchmarking The Imbalanced Behavior of Deep Learning Based Optical Flow Estimators 基于深度学习的光流估计器不平衡行为的基准测试

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00035

Stefano Savian, Mehdi Elahi, T. Tillo

{"title":"Benchmarking The Imbalanced Behavior of Deep Learning Based Optical Flow Estimators","authors":"Stefano Savian, Mehdi Elahi, T. Tillo","doi":"10.1109/SITIS.2019.00035","DOIUrl":"https://doi.org/10.1109/SITIS.2019.00035","url":null,"abstract":"Optical Flow (OF) estimation is an important task which could be effectively used for a variety of Computer Vision (CV) applications. While a range of techniques have been already proposed, however accurately estimating the OF is still a very challenging task. The most recent approaches for OF estimation exploit advanced Deep Learning techniques which have resulted in a shift in the paradigm. These techniques have shown substantial improvements particularly in the case of large displacements, brightness change, and non-rigid motion. However, these approaches are data-driven and hence they can be biased towards the specific training data, which could in turn lead to considerable inaccuracy of the estimated OF. In this paper, we address this problem and provide a novel benchmark that can be used to identify and to measure the bias magnitude of the OF estimation. We have performed several experiments based on public datasets (Monkaa and Sintel) as well as on data designed on purpose 1. The results have shown that OF estimation based on some of the state-of-the-art deep learning techniques strongly depend on factors such as motion orientation within the data. Indeed, we have observed substantial degree of bias toward certain directions of motion. The framework can help researchers and practitioners in order to develop more effective data augmentation techniques and training schedules for deep learning based optical flow estimators.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124319970","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 Novel Approach to Detect Outer Retinal Tubulation Using U-Net in SD-OCT Images 一种基于SD-OCT图像U-Net检测视网膜外管状的新方法

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00096

István Megyeri, Melinda Katona, L. G. Nyúl

{"title":"A Novel Approach to Detect Outer Retinal Tubulation Using U-Net in SD-OCT Images","authors":"István Megyeri, Melinda Katona, L. G. Nyúl","doi":"10.1109/SITIS.2019.00096","DOIUrl":"https://doi.org/10.1109/SITIS.2019.00096","url":null,"abstract":"Optical Coherence Tomography (OCT) has become a basic non-invasive tool in diagnosing and following different types of eye diseases. This technique can produce high-resolution cross-sectional images of retinal layers. Outer retinal tubulation (ORT) is one of the detectable biomarker by SD-OCT. ORTs defined as hyporeflective, tubular structures with hyperreflective borders or reversed within the retina and appear in many retinal diseases, including age-related macular degeneration (AMD). Our aim is to develop an automatic method that can efficiently characterize ORT biomarker. Detection of this biomarker can be challenging because of its variable size, location, and reflectivity. In this paper, we present a fully convolutional U-Net based architecture to detect ORT. The proposed approach is evaluated using a dataset annotated by ophthalmologists. One of the main challenges was the limited amount of training data that we resolve with real-time augmentation during training and using nested cross-validation. Our method achieved near human performance reaching an overall object-based recall score of 0.847 and Dice score of 0.579 on the test set.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124320451","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

MeltdownCrisis: Dataset of Autistic Children During Meltdown Crisis 熔毁危机:熔毁危机期间自闭症儿童的数据集

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00048

Marwa Masmoudi, Salma Kammoun Jarraya, Mohamed Hammami

{"title":"MeltdownCrisis: Dataset of Autistic Children During Meltdown Crisis","authors":"Marwa Masmoudi, Salma Kammoun Jarraya, Mohamed Hammami","doi":"10.1109/SITIS.2019.00048","DOIUrl":"https://doi.org/10.1109/SITIS.2019.00048","url":null,"abstract":"No one refutes the importance of datasets in the development of any new approach. Despite their importance, datasets in computer vision remain insufficient for some applications. Presently, very limited autism datasets associated with clinical tests or screening are available, and most of them are genetic in nature. However, there is no database that combines both the abnormal facial expressions and the aggressive behaviors of an autistic child during Meltdown crisis. This paper introduces a Meltdown Crisis, a new and rich dataset that can be used for the evaluation/development of computer vision-based applications pertinent to children who suffer of autism as security tool, e.g. Meltdown crisis detection. In particular, the \"MeltdownCrisis\" dataset includes video streams captured with Kinect which offers a wide range of visual information. It is divided on a facial expressions data and physical activities data. The current \"MeltdownCrisis \" dataset version covers several Meltdown crisis scenarios of autistic children along various normal state scenarios grouped into one set. Each scenario is represented through a rich set of features that can be extracted from Kinect camera.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124475902","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

On the Detection of Video's Ethnic Vietnamese Thai Dance Movements 录像中越南民族泰式舞蹈动作的检测

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00064

Tung Pham Thanh, S. Benferhat, M. Chau, T. Ma, Karim Tabia, L. T. Ha

引用次数: 0

Enhanced Morphological Filtering for Wavelet-Based Changepoint Detection 基于小波变换点检测的增强形态学滤波

2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 2019-11-01 DOI: 10.1109/SITIS.2019.00021

M. Stasolla, X. Neyt

引用次数: 1