Asma Omri, Karim Benouaret, Mohamed Nazih Omri, D. Benslimane
The acceptance of open data practices by individuals and organizations lead to an enormous explosion in data production on the Internet. The access to a large number of these data is carried out through Web services, which provide a standard way to interact with data. This class of services is known as data services. In this context, users' queries often require the composition of multiple data services to be answered. On the other hand, the data returned by a data service is not always certain due to various raisons, e.g., the service accesses different data sources, privacy constraints, etc. In this paper, we study the basic activities of data services that are affected by the uncertainty of data, more specifically, modeling, invocation and composition. We propose a possibilistic approach that treats the uncertainty in all these activities.
{"title":"Querying Data Services in an Uncertain Environment: A Possibilistic-Based Approach","authors":"Asma Omri, Karim Benouaret, Mohamed Nazih Omri, D. Benslimane","doi":"10.1109/SITIS.2016.47","DOIUrl":"https://doi.org/10.1109/SITIS.2016.47","url":null,"abstract":"The acceptance of open data practices by individuals and organizations lead to an enormous explosion in data production on the Internet. The access to a large number of these data is carried out through Web services, which provide a standard way to interact with data. This class of services is known as data services. In this context, users' queries often require the composition of multiple data services to be answered. On the other hand, the data returned by a data service is not always certain due to various raisons, e.g., the service accesses different data sources, privacy constraints, etc. In this paper, we study the basic activities of data services that are affected by the uncertainty of data, more specifically, modeling, invocation and composition. We propose a possibilistic approach that treats the uncertainty in all these activities.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117236708","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}
Yashas Annadani, Vijayakrishna Naganoor, A. Jagadish, K. Chemmangat
Categorisation of huge amount of data on the multimedia platform is a crucial task. In this work, we propose a novel approach to address the subtle problem of selfie detection for image database segregation on the web, given rapid rise in the number of selfies being clicked. A Convolutional Neural Network (CNN) is modeled to learn a synergy feature in the common subspace of head and shoulder orientation, derived from Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG) features respectively. This synergy was captured by projecting the aforementioned features using Canonical Correlation Analysis (CCA). We show that the resulting network's convolutional activations in the neighbourhood of spatial keypoints captured by SIFT are discriminative for selfie-detection. In general, proposed approach aids in capturing intricacies present in the image data and has the potential for usage in other subtle image analysis scenarios apart from just selfie detection. We investigate and analyse the performance of the popular CNN architectures (GoogleNet, Alexnet), used for other image classification tasks, when subjected to the task of detecting the selfies on the multimedia platform. The results of the proposed approach are compared with these popular architectures on a dataset of ninety thousand images comprising of roughly equal number of selfies and non-selfies. Experimental results on this dataset shows the effectiveness of the proposed approach.
对多媒体平台上的海量数据进行分类是一项至关重要的任务。在这项工作中，我们提出了一种新的方法来解决网络上图像数据库隔离的自拍检测的微妙问题，因为自拍被点击的数量迅速增加。对卷积神经网络(CNN)进行建模，分别从局部二值模式(Local Binary Pattern, LBP)和方向梯度直方图(Histogram of Oriented Gradients, HOG)特征中提取头部和肩部方向共同子空间中的协同特征。这种协同作用是通过使用典型相关分析(CCA)预测上述特征来实现的。我们证明了所得网络在SIFT捕获的空间关键点附近的卷积激活对于自检测具有区别性。总的来说，所提出的方法有助于捕获图像数据中存在的复杂性，并且除了自拍检测之外，还具有在其他微妙图像分析场景中使用的潜力。我们调查和分析了用于其他图像分类任务的流行CNN架构(GoogleNet, Alexnet)在检测多媒体平台上的自拍照任务时的性能。将所提出的方法的结果与这些流行的架构在9万张图像的数据集上进行比较，这些图像包括大致相同数量的自拍照和非自拍照。在该数据集上的实验结果表明了该方法的有效性。
{"title":"Selfie Detection by Synergy-Constraint Based Convolutional Neural Network","authors":"Yashas Annadani, Vijayakrishna Naganoor, A. Jagadish, K. Chemmangat","doi":"10.1109/SITIS.2016.61","DOIUrl":"https://doi.org/10.1109/SITIS.2016.61","url":null,"abstract":"Categorisation of huge amount of data on the multimedia platform is a crucial task. In this work, we propose a novel approach to address the subtle problem of selfie detection for image database segregation on the web, given rapid rise in the number of selfies being clicked. A Convolutional Neural Network (CNN) is modeled to learn a synergy feature in the common subspace of head and shoulder orientation, derived from Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG) features respectively. This synergy was captured by projecting the aforementioned features using Canonical Correlation Analysis (CCA). We show that the resulting network's convolutional activations in the neighbourhood of spatial keypoints captured by SIFT are discriminative for selfie-detection. In general, proposed approach aids in capturing intricacies present in the image data and has the potential for usage in other subtle image analysis scenarios apart from just selfie detection. We investigate and analyse the performance of the popular CNN architectures (GoogleNet, Alexnet), used for other image classification tasks, when subjected to the task of detecting the selfies on the multimedia platform. The results of the proposed approach are compared with these popular architectures on a dataset of ninety thousand images comprising of roughly equal number of selfies and non-selfies. Experimental results on this dataset shows the effectiveness of the proposed approach.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130731721","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}
A. Giannakidis, K. Kamnitsas, V. Spadotto, J. Keegan, Gillian Smith, B. Glocker, D. Rueckert, S. Ernst, M. Gatzoulis, D. Pennell, S. Babu-Narayan, D. Firmin
Cardiac magnetic resonance (CMR) is regarded as the reference examination for cardiac morphology in tetralogy of Fallot (ToF) patients allowing images of high spatial resolution and high contrast. The detailed knowledge of the right ventricular anatomy is critical in ToF management. The segmentation of the right ventricle (RV) in CMR images from ToF patients is a challenging task due to the high shape and image quality variability. In this paper we propose a fully automatic deep learning-based framework to segment the RV from CMR anatomical images of the whole heart. We adopt a 3D multi-scale deep convolutional neural network to identify pixels that belong to the RV. Our robust segmentation framework was tested on 26 ToF patients achieving a Dice similarity coefficient of 0.8281±0.1010 with reference to manual annotations performed by expert cardiologists. The proposed technique is also computationally efficient, which may further facilitate its adoption in the clinical routine.
{"title":"Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network","authors":"A. Giannakidis, K. Kamnitsas, V. Spadotto, J. Keegan, Gillian Smith, B. Glocker, D. Rueckert, S. Ernst, M. Gatzoulis, D. Pennell, S. Babu-Narayan, D. Firmin","doi":"10.1109/SITIS.2016.16","DOIUrl":"https://doi.org/10.1109/SITIS.2016.16","url":null,"abstract":"Cardiac magnetic resonance (CMR) is regarded as the reference examination for cardiac morphology in tetralogy of Fallot (ToF) patients allowing images of high spatial resolution and high contrast. The detailed knowledge of the right ventricular anatomy is critical in ToF management. The segmentation of the right ventricle (RV) in CMR images from ToF patients is a challenging task due to the high shape and image quality variability. In this paper we propose a fully automatic deep learning-based framework to segment the RV from CMR anatomical images of the whole heart. We adopt a 3D multi-scale deep convolutional neural network to identify pixels that belong to the RV. Our robust segmentation framework was tested on 26 ToF patients achieving a Dice similarity coefficient of 0.8281±0.1010 with reference to manual annotations performed by expert cardiologists. The proposed technique is also computationally efficient, which may further facilitate its adoption in the clinical routine.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133594600","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}
The interruption of video playback continuity, also identified from users' perspective as rebuffering or stalling, is one of the key phenomena that can hinder user experience during streaming video services. Its subjective observation, however, may change over time, similarly to most human factors. In this paper we present the results of a research designed to investigate how the perception of rebuffering during video streams varies over time, and how it correlates with the perceptual abilities of individuals. The subjective tests were performed on an autostereoscopic, glasses-free 3D display, as our experiment also studies the depth distance and thus the perceived size of objects in video content with a given motion during stalling events.
{"title":"Times Change, Stalling Stays: Subjective Quality Assessment over Time of Stalling in Autostereoscopic 3D Video Services","authors":"P. A. Kara, M. Martini, C. Hewage, F. Felisberti","doi":"10.1109/SITIS.2016.129","DOIUrl":"https://doi.org/10.1109/SITIS.2016.129","url":null,"abstract":"The interruption of video playback continuity, also identified from users' perspective as rebuffering or stalling, is one of the key phenomena that can hinder user experience during streaming video services. Its subjective observation, however, may change over time, similarly to most human factors. In this paper we present the results of a research designed to investigate how the perception of rebuffering during video streams varies over time, and how it correlates with the perceptual abilities of individuals. The subjective tests were performed on an autostereoscopic, glasses-free 3D display, as our experiment also studies the depth distance and thus the perceived size of objects in video content with a given motion during stalling events.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124475598","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}
P. A. Kara, P. Kovács, Suren Vagharshakyan, M. Martini, A. Barsi, T. Balogh, A. Chuchvara, Ahmed Chehaibi
The quality of visual contents displayed on 3D autostereoscopic displays – such as light field displays – essentially depend on factors that are not present in case of 3D stereoscopic or 2D ones, like angular resolution. A higher number of views in a given field of view enables a smoother, continuous motion parallax, but evidently requires more resources to transmit and display. However, in several cases a sufficiently high number of views might not even be available, thus light field reconstruction is required to increase the density of intermediate views. In this paper we introduce the results of a research aiming to measure the perceptual difference between light field reconstruction and different angular resolutions via a series of subjective image quality assessments. The analysis also calls attention to transmission requirements of content for light field displays.
{"title":"The Effect of Light Field Reconstruction and Angular Resolution Reduction on the Quality of Experience","authors":"P. A. Kara, P. Kovács, Suren Vagharshakyan, M. Martini, A. Barsi, T. Balogh, A. Chuchvara, Ahmed Chehaibi","doi":"10.1109/SITIS.2016.128","DOIUrl":"https://doi.org/10.1109/SITIS.2016.128","url":null,"abstract":"The quality of visual contents displayed on 3D autostereoscopic displays – such as light field displays – essentially depend on factors that are not present in case of 3D stereoscopic or 2D ones, like angular resolution. A higher number of views in a given field of view enables a smoother, continuous motion parallax, but evidently requires more resources to transmit and display. However, in several cases a sufficiently high number of views might not even be available, thus light field reconstruction is required to increase the density of intermediate views. In this paper we introduce the results of a research aiming to measure the perceptual difference between light field reconstruction and different angular resolutions via a series of subjective image quality assessments. The analysis also calls attention to transmission requirements of content for light field displays.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124991159","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}
This study aimed to design a model for automatic identification of emotion from spontaneous communication using the acoustic characteristics of human speech. An experimental setup to collect and annotate call center Amharic telephone dialogs containing natural emotions is presented. These dialogs, involve 35 subjects (18 male and 17 female), are first manually decomposed into speaker turns and then segmented into intermediate chunks to be used as the analysis unit for feature calculation. Open class annotation is carried out by 3 professional psychologists and the various emotional states are mapped onto 4 cover classes, and a Majority Voting (MV) technique is applied to decide perceived emotion in each chunk. A total of 170 acoustic features consisting of prosodic, spectral and voice quality features are extracted from each chunk. An optimal feature set representing emotion (i.e. 33 all together) are selected through the use of generic algorithm and used to train Multilayer Perceptron Neural Network (MLPNN) classifier. A prototype application has been developed and the classification performance has been evaluated based on extracted features. Our preliminary speech emotion recognition model exhibits an average accuracy of 72.4% in identifying Anger, Fear, Positive and Sadness emotions.
{"title":"Emotion Identification from Spontaneous Communication","authors":"Fekade Getahun Taddesse, Mikiyas Kebede","doi":"10.1109/SITIS.2016.32","DOIUrl":"https://doi.org/10.1109/SITIS.2016.32","url":null,"abstract":"This study aimed to design a model for automatic identification of emotion from spontaneous communication using the acoustic characteristics of human speech. An experimental setup to collect and annotate call center Amharic telephone dialogs containing natural emotions is presented. These dialogs, involve 35 subjects (18 male and 17 female), are first manually decomposed into speaker turns and then segmented into intermediate chunks to be used as the analysis unit for feature calculation. Open class annotation is carried out by 3 professional psychologists and the various emotional states are mapped onto 4 cover classes, and a Majority Voting (MV) technique is applied to decide perceived emotion in each chunk. A total of 170 acoustic features consisting of prosodic, spectral and voice quality features are extracted from each chunk. An optimal feature set representing emotion (i.e. 33 all together) are selected through the use of generic algorithm and used to train Multilayer Perceptron Neural Network (MLPNN) classifier. A prototype application has been developed and the classification performance has been evaluated based on extracted features. Our preliminary speech emotion recognition model exhibits an average accuracy of 72.4% in identifying Anger, Fear, Positive and Sadness emotions.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"35 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":"132225708","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}
The computation of the European options price in a Black-Scholes market, characterized by the presence of no arbitrage condition, is an important applicative problem. In this paper we are interested in highlighting some numerical issues related to this problem. The proposed procedure is mainly divided into three parts: the test of the lognomality of the risk asset, the estimation of the volatility of the underlying and, finally, the determination of the price. As concerns the first point, we propose the adoption of the the Shapiro-Wilk test, in the second one we suggest to estimate the volatility by the sample standard deviation and in the third point we apply the Black-Scholes formula and we introduce an approximation for a Normal function value by means of a quadrature formula.
{"title":"Numerical Remarks on the Estimation of the Option Price","authors":"S. Cuomo, R. Campagna, V. D. Somma, G. Severino","doi":"10.1109/SITIS.2016.123","DOIUrl":"https://doi.org/10.1109/SITIS.2016.123","url":null,"abstract":"The computation of the European options price in a Black-Scholes market, characterized by the presence of no arbitrage condition, is an important applicative problem. In this paper we are interested in highlighting some numerical issues related to this problem. The proposed procedure is mainly divided into three parts: the test of the lognomality of the risk asset, the estimation of the volatility of the underlying and, finally, the determination of the price. As concerns the first point, we propose the adoption of the the Shapiro-Wilk test, in the second one we suggest to estimate the volatility by the sample standard deviation and in the third point we apply the Black-Scholes formula and we introduce an approximation for a Normal function value by means of a quadrature formula.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115665883","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}
The Detection of the vehicles on the road for the classification of the vehicles. The image processing by Blob Analysis for careful all the time, because of safety while driving is important. It's help to reduce accidents on the road, this article presents a program of on-road driving in a vehicle. When processed by the image processing and display counting when the object of interest when they move into the period, accounting for 96% of accuracy.
{"title":"The System Vehicle of Application Detector for Categorize Type","authors":"Siriruang Phatchuay, Worawut Yimyam","doi":"10.1109/SITIS.2016.114","DOIUrl":"https://doi.org/10.1109/SITIS.2016.114","url":null,"abstract":"The Detection of the vehicles on the road for the classification of the vehicles. The image processing by Blob Analysis for careful all the time, because of safety while driving is important. It's help to reduce accidents on the road, this article presents a program of on-road driving in a vehicle. When processed by the image processing and display counting when the object of interest when they move into the period, accounting for 96% of accuracy.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121206001","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}
The rapid growth of video data demands both effective and efficient video summarization methods so that users are allowed to speedily browse and comprehend a large amount of video content. Hence, it is very challenging to store and access such audiovisual information in real time where an immense amount of recorded video content is rising within one second. In this paper we proposed an equal partition based clustering technique for summarizing the events in videos which can work better for real time applications (for e.g., surveillance video in various security systems). In clustering, the difficulty is to obtain the optimal set of clusters, which is gained by implementing Davies-Bouldin Index, a cluster validation technique which permits the users with free parameter based video summarization method for selecting the numbers of key–frames without incurring additional computational cost. The qualitative as well as quantitative evaluation is done in order to compare the performances of our proposed model and state-of-theart models. Experimental results on two benchmark datasets with various types of videos expose that the proposed method outperforms the state-of-the-art models with the best Precision and F–measure.
{"title":"Equal Partition Based Clustering Approach for Event Summarization in Videos","authors":"Krishan Kumar, D. Shrimankar, Navjot Singh","doi":"10.1109/SITIS.2016.27","DOIUrl":"https://doi.org/10.1109/SITIS.2016.27","url":null,"abstract":"The rapid growth of video data demands both effective and efficient video summarization methods so that users are allowed to speedily browse and comprehend a large amount of video content. Hence, it is very challenging to store and access such audiovisual information in real time where an immense amount of recorded video content is rising within one second. In this paper we proposed an equal partition based clustering technique for summarizing the events in videos which can work better for real time applications (for e.g., surveillance video in various security systems). In clustering, the difficulty is to obtain the optimal set of clusters, which is gained by implementing Davies-Bouldin Index, a cluster validation technique which permits the users with free parameter based video summarization method for selecting the numbers of key–frames without incurring additional computational cost. The qualitative as well as quantitative evaluation is done in order to compare the performances of our proposed model and state-of-theart models. Experimental results on two benchmark datasets with various types of videos expose that the proposed method outperforms the state-of-the-art models with the best Precision and F–measure.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127332857","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}
The purpose of this paper was to devise a way to alert drowsy drivers in the act of driving. One of the causes of car accidents comes from drowsiness of the driver. Therefore, this study attempted to address the issue by creating an experiment in order to calculate the level of drowsiness. A requirement for this paper was the utilisation of a Raspberry Pi Camera and Raspberry Pi 3 module, which were able to calculate the level of drowsiness in drivers. The frequency of head tilting and blinking of the eyes was used to determine whether or not a driver felt drowsy. With an evaluation on ten volunteers, the accuracy of face and eye detection was up to 99.59 percent.
{"title":"Driver Drowsiness Detection Using Eye-Closeness Detection","authors":"Oraan Khunpisuth, Taweechai Chotchinasri, Varakorn Koschakosai, Narit Hnoohom","doi":"10.1109/SITIS.2016.110","DOIUrl":"https://doi.org/10.1109/SITIS.2016.110","url":null,"abstract":"The purpose of this paper was to devise a way to alert drowsy drivers in the act of driving. One of the causes of car accidents comes from drowsiness of the driver. Therefore, this study attempted to address the issue by creating an experiment in order to calculate the level of drowsiness. A requirement for this paper was the utilisation of a Raspberry Pi Camera and Raspberry Pi 3 module, which were able to calculate the level of drowsiness in drivers. The frequency of head tilting and blinking of the eyes was used to determine whether or not a driver felt drowsy. With an evaluation on ten volunteers, the accuracy of face and eye detection was up to 99.59 percent.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"43 243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124968542","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}
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