Procedings do XV Simpósio Brasileiro de Automação Inteligente, 2021
The occurrence of high impedance faults (HIF) in primary distribution networks represents a dange... more The occurrence of high impedance faults (HIF) in primary distribution networks represents a danger to the safety of people, equipment, and animals. However, protection devices close to the distribution network are not able to be sensitized by this type of defect, in most cases. This work presents an integrated strategy for the classification and detection of HIF, based on the use of classifiers based on supervised learning algorithms, such as K-nearest neighbors, Support Vector Machines and Ensemble. An improved fault model was used to emulate random behaviors, and especially intermittency for high impedance faults. The residual current was monitored, and its characteristics were extracted using the Short-Time Fourier Transform (STFT). A temporal consistency logic was applied to the detection stage. The functioning of the presented algorithm was carried out through several simulations in a 20 kV distribution system. Resumo: A ocorrência de faltas de alta impedância (FAI) em redes de distribuição primárias representa um perigo para a segurança das pessoas, equipamentos e animais. No entanto, dispositivos de proteção junto a rede de distribuição não são capazes de serem sensibilizados por esse tipo de defeito, na maioria das vezes. Este trabalho apresenta uma estratégia integrada de classificação e detecção de FAI, baseado no uso de classificadores baseados em algoritmos de aprendizado supervisionado, tais como K-nearest neighbors, Support Vector Machines e Ensemble. Um modelo de falta aprimorado foi usado para emular comportamentos de aleatoriedade, e especialmente intermitência de faltas de alta impedância. A corrente residual foi monitorada, e a extração de suas características foi realizada a partir da Short-Time Fourier Transform (STFT). Uma lógica de consistência temporal foi aplicada ao estágio de detecção. O funcionamento do algoritmo apresentado foi realizado através de diversas simulações em um sistema de distribuição de 20 kV.
2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018
The fusion of visible-light and infrared videos has applications in several areas, and is an acti... more The fusion of visible-light and infrared videos has applications in several areas, and is an active research topic. To this end, it is common to employ complex fusion methods that take into account spatial and/or temporal information in the videos. In this paper we propose a video fusion method that is based on a motion-compensated, two-band temporal sub-band decomposition. The alignment provided by the motion vectors, besides providing a reduction in the registration errors of the input images, allows the use of a simple fusion rule to the temporal sub-bands. The results indicate that the use of the proposed exploration of the temporal information alone is quite effective, and gives objective fusion quality results that compare favorably to more sophisticated methods based on complete spatiotemporal information.
IEEE Transactions on Circuits and Systems I: Regular Papers, 2021
Sign language is the main type of communication of the deaf community. However, most people do no... more Sign language is the main type of communication of the deaf community. However, most people do not know this language, which causes communication problems for many people. Many technological solutions have been proposed to overcome this issue. Some use the concept of wearable devices, but gesture recognition in a video sequence is a cheaper and less intrusive solution. In this work, we address the problem of gesture recognition in video. To do so, we employ a two-step method with feature space mapping and classification. First, the body parts of each subject in a video are segmented through a deep neural network architecture. Then, we use Gait Energy Image to encode the motion of the body parts in a compact feature space. Small datasets are usually a problem in this type of application, leading to sparse representation in the feature space. To contour this problem, we evaluate SMOTE as a data augmentation technique in the feature space and classical dimensionality reduction techniques. We evaluate our method on three challenging Brazilian sign language (Libras) datasets, CEFET/RJ-Libras, MINDS-Libras, and LIBRAS-UFOP, achieving global accuracies of 85.40±3.13%, 84.66±1.78%, and 64.91±3.79%, respectively, with singular value decomposition and support vector machine.
2020 Latin American Robotics Symposium (LARS), 2020 Brazilian Symposium on Robotics (SBR) and 2020 Workshop on Robotics in Education (WRE), 2020
Communication is a basic human necessity, but the deaf community is still facing some barriers. I... more Communication is a basic human necessity, but the deaf community is still facing some barriers. In Brazil, there are about 9.7 million people with some degree of hearing impairment but most Brazilians do not know the Brazilian Sign Language (Libras). Wearable gadgets like gloves or bracelets with sensors are a good tool to help in communication, but these solutions are pricey or intrusive. On the other hand, computer vision solutions are cheaper but challenging mainly due to the absence of reliable video databases. In this work, we propose a video database compounded by different signs, with various backgrounds, and different speakers. We also developed a system to perform computer vision-based sign recognition using the k-nearest neighbors (K-NN) and random forest (RF). In our tests, we achieved an average accuracy of 65.81 % in multiclass classification.
Anais do XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2021
Massive MIMO systems have received a growing interest since the apogee of 5G and the perspective ... more Massive MIMO systems have received a growing interest since the apogee of 5G and the perspective of 6G. Massive MIMO allows an efficient usage of spectral resources and provides higher data rates. When the number of antennas increases, the energy consumption and the hardware cost in the base station also increase. The high energy consumption and processing may be addressed through the selection of antennas. Among various possible structures in the literature, the present work proposes the combination of full-array architecture to make a virtual sectorization and antenna selection using matching pursuit. The algorithm was tested in different channels with complexity reduction in our tests while maintaining bit-error rate in most scenarios.
Anais do XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2021
In Brazil, there are around 10 million hard of hearing and deaf people. However, the majority of ... more In Brazil, there are around 10 million hard of hearing and deaf people. However, the majority of Brazilians are not fluent in the Brazilian Sign Language (Libras). Many members of the hearing impaired and deaf community have communication issues in everyday life situations. Technological solutions can aid in mitigating this problem. This work proposes a semi-supervised method to identify and classify signals in Libras from Youtube videos. The routine starts by segmenting the videos through a measure of movement intensity. We catalog the video segments according to the corresponding subtitles, which we extract by employing Optical Character Recognition (OCR) if embedded. It composes an ad-hoc dataset that we use to train a Libras recognition system. A Convolutional Neural Network (CNN) performs feature extraction frame-by-frame, and a Recurrent Neural Network (RNN) models the time correlation between the features, thus classifying the signal. The proposed method can achieve accuracy up to 61.6% in the ad-hoc dataset used in this work.
2021 IEEE 12th Latin America Symposium on Circuits and System (LASCAS), 2021
A common problem faced by the deaf community is that most people do not know sign language so com... more A common problem faced by the deaf community is that most people do not know sign language so communication is still an issue. This is not different in Brazil, where the sign language is called Libras. Many technological solutions are being proposed but gesture recognition in video sequences is the less intrusive one. In this work, we address the problem of recognizing gestures of Libras in video sequences. To do so, we first segment the body parts of the person in the video using a deep neural network architecture, in a frame by frame fashion. Then, we employ Gait Energy Image to encode the motion into a compact feature space. These features are fed to a classifier to attribute a label to each video. In our experiments, we achieved the 53.90±5.48% of accuracy using K-Nearest Neighbors and 79.57±2.39% using Random Forest in the best configuration across the 24 dataset classes.
2021 14th IEEE International Conference on Industry Applications (INDUSCON), 2021
The occurrence of high impedance faults (HIF) in primary distribution grid poses a danger to the ... more The occurrence of high impedance faults (HIF) in primary distribution grid poses a danger to the safety of people, equipment, and animals. However, protection devices along the distribution network are not capable of being sensitized by this type of defect, most of the time. This work presents an integrated strategy of HIF classification and detection, based on the use of Support Vector Machines. An improved fault model was used to emulate randomness behaviors, and especially intermittence of high impedance faults. The residual current is monitored, and the extraction of its characteristics is performed with Short-Time Fourier Transform. A logic of temporal consistency has been applied to the detection stage. The presented algorithm´s operation was achieved throughout several simulations in a 20 kV distribution system.
Multidimensional Systems and Signal Processing, 2017
In general, the fusion of visible-light and infrared images produces a composite representation w... more In general, the fusion of visible-light and infrared images produces a composite representation where both data are pictured in a single image. The successful development of image/video fusion algorithms relies on realistic infrared/visible-light datasets. To the best of our knowledge, there is a particular shortage of databases with registered and synchronized videos from the infrared and visible-light spectra suitable for image/video fusion research. To address this need we recorded an image/video fusion database using infrared and visible-light cameras under varying illumination conditions. Moreover, different scenarios have been defined to better challenge the fusion methods, with various contexts and contents providing a wide variety of meaningful data for fusion purposes, including nonplanar scenes, where objects appear on different depth planes. However, there are several difficulties in creating datasets for research in infrared/visible-light image fusion. Camera calibration, registration, and synchronization can be listed as important steps of this task. In particular, image registration between imagery from sensors of different spectral bands imposes additional difficulties, as it is very challenging to solve the correspondence problem between such images. Motivated by these challenges, this work introduces a novel spatiotemporal video registration method capable of generating registered and temporally aligned infrared/visible-light video sequences. The proposed workflow improves the registration ac
In this paper we investigate how visualization factors, such as disparity, mobility, angular reso... more In this paper we investigate how visualization factors, such as disparity, mobility, angular resolution and viewpoint interpolation, influence the Quality of Experience (QoE) in a stereoscopic multiview environment. In order to do so, we set up a dedicated testing room and conducted subjective experiments. We also developed a framework that emulates a super-multiview environment. This framework can be used to investigate and assess the effects of angular resolution and viewpoint interpolation on the quality of experience produced by multiview systems, and provide relevant cues as to how the baselines of cameras and interpolation strategies in such systems affect user experience. Aspects such as visual comfort, model fluidity, sense of immersion, and the 3D experience as a whole have been assessed for several test cases. Obtained results suggest that user experience in an motion parallax environment is not as critically influenced by configuration parameters such as disparity as initially thought. In addition, extensive subjective tests have indicated that while users are very sensitive to angular resolution in multiview 3D systems, this sensitivity tends not to be as critical when a user is performing a task that involves a great amount of interaction with the multiview content. These tests have also indicated that interpolating intermediate viewpoints can be effective in reducing the required view density without degrading the perceived QoE.
Journal of Communication and Information Systems, 2016
The increasing exploitation of natural resources under water, particularly in the sea, has ignite... more The increasing exploitation of natural resources under water, particularly in the sea, has ignited the development of many technological advances in the domains of environmental monitoring, oil and gas exploration, warfare, among others. In all these domains, underwater wireless communications play an important role, where the technologies available rely on radiofrequency, optical, and acoustic transmissions. This paper surveys key features inherent to these communication technologies, putting into perspective their technical aspects, current research challenges, and to-be-explored potential. I. INTRODUCTION Underwater wireless communications present new and distinct challenges when compared to wired and wireless communications through the atmosphere, requiring sophisticated communication devices to achieve relatively low transmission rates, even over short distances. Indeed, the underwater environment possesses a number of distinguishing features that make it unique and rather different from terrestrial radio propagation where traditional communication systems are deployed. Under water, several phenomena may influence communications, such as salt concentration, pressure, temperature, amount of light, winds and their effects on waves, just to mention a few [1], [2]. Despite all challenges, wireless communications certainly play an important role in practical underwater systems. Monitoring different phenomena in underwater environment is relevant in many different applications, such as oil and gas exploration, coastal security, environmental impact surveillance, navigation, and ocean-pollution control [3]. Specific examples include transmission of data among devices, such as AUV (autonomous underwater vehicle) to AUV and buoy to AUV, particularly those employing wireless links. In fact, an entire underwater wireless communication network could
Big data analytics, applied in the industry to leverage data collection, processing and analysis,... more Big data analytics, applied in the industry to leverage data collection, processing and analysis, can allow a better understanding of production system's abnormal behavior. This knowledge is essential for the adoption of a proactive maintenance approach instead of conventional time-based strategies, leading to a paradigm shift towards Condition-Based Maintenance (CBM) since decision is now based on the usage of a huge, diverse, and dynamic amounts of data as a means to optimize operational costs. This paper reports an investigation of the emerging aspects in the design and implementation of big data analytics solutions for offshore installations in order to allow predictive maintenance practices. Condition-based maintenance focuses on performing interventions based on the actual and future states (health) of a system by monitoring the underlying deterioration processes. One of the building blocks of a CBM design and implementation is the prognostic approach/system, which aims to...
2013 IEEE International Conference on Image Processing, 2013
The accurate geometric calibration of thermal infrared (IR) cameras is of vital importance in man... more The accurate geometric calibration of thermal infrared (IR) cameras is of vital importance in many computer vision applications. In general, the calibration procedure consists of localizing a set of calibration points within a calibration image. This set is subsequently used to solve for the camera parameters. However, due to the physical limitations of the IR acquisition process, the localization of the calibration points often poses difficulties, subsequently leading to unsatisfying calibration results. In this work a novel IR camera calibration approach is introduced. It is able to localize the calibration points within the images of a conventional calibration board consisting of miniature light-bulbs with improved accuracy. Our algorithm models the radiation pattern of each light bulb as an ellipse and considers the center of mass of the extracted ellipsoidal region as the starting calibration point, which is refined iteratively using alternating mappings to and from an undistorted grid model. The proposed processing chain leads to a significantly reduced calibration error when compared to the state-of-the-art. Furthermore, the proposed methodology can also be used to calibrate visible-light cameras thus being suitable for the calibration of multiple camera rigs involving both visible-light and IR cameras.
In this work we investigate how the angular resolution of a camera system influences the user exp... more In this work we investigate how the angular resolution of a camera system influences the user experience in immersive, interactive 3D applications. In order to investigate that, we developed a parallax-based framework that renders 3D models and tracks the user position by detecting LEDs or infrared markers attached to 3D glasses. The presented framework allows to simulate a system with an arbitrary number of viewpoints by changing the resolution of the users' tracked position. Extensive subjective tests were conducted where users interacted with the 3D models while the number of available viewpoints (angular resolution) was changed.
Traditional temporal video alignment techniques depend on the existence of a sufficient number of... more Traditional temporal video alignment techniques depend on the existence of a sufficient number of mutual scene characteristics to perform temporal synchronization. However, for video sequences originating from different spectral modalities such information may fail to exist, subsequently leading to unreliable alignment results. In this work, a novel, practical approach for the temporal alignment of infrared (IR) and visiblelight video sequences is introduced. Utilizing a planar alignment device consisting of an array of miniature light bulbs, we propose to increase the number of mutual feature points within the frames of a temporally misaligned IR/visible-light video sequence pair. Thereby, we provide an abundant number of mutual scene characteristics which can subsequently be used to determine the time-shift between the two sequences. Tests with five different IR/visible-light sequence pairs suggest that our technique is able to estimate the temporal offset with a very high confidence level. Furthermore, due to the simplicity of the construction of the alignment board, the proposed framework can be seamlessly integrated within a stereo camera calibration scheme.
Procedings do XV Simpósio Brasileiro de Automação Inteligente, 2021
The occurrence of high impedance faults (HIF) in primary distribution networks represents a dange... more The occurrence of high impedance faults (HIF) in primary distribution networks represents a danger to the safety of people, equipment, and animals. However, protection devices close to the distribution network are not able to be sensitized by this type of defect, in most cases. This work presents an integrated strategy for the classification and detection of HIF, based on the use of classifiers based on supervised learning algorithms, such as K-nearest neighbors, Support Vector Machines and Ensemble. An improved fault model was used to emulate random behaviors, and especially intermittency for high impedance faults. The residual current was monitored, and its characteristics were extracted using the Short-Time Fourier Transform (STFT). A temporal consistency logic was applied to the detection stage. The functioning of the presented algorithm was carried out through several simulations in a 20 kV distribution system. Resumo: A ocorrência de faltas de alta impedância (FAI) em redes de distribuição primárias representa um perigo para a segurança das pessoas, equipamentos e animais. No entanto, dispositivos de proteção junto a rede de distribuição não são capazes de serem sensibilizados por esse tipo de defeito, na maioria das vezes. Este trabalho apresenta uma estratégia integrada de classificação e detecção de FAI, baseado no uso de classificadores baseados em algoritmos de aprendizado supervisionado, tais como K-nearest neighbors, Support Vector Machines e Ensemble. Um modelo de falta aprimorado foi usado para emular comportamentos de aleatoriedade, e especialmente intermitência de faltas de alta impedância. A corrente residual foi monitorada, e a extração de suas características foi realizada a partir da Short-Time Fourier Transform (STFT). Uma lógica de consistência temporal foi aplicada ao estágio de detecção. O funcionamento do algoritmo apresentado foi realizado através de diversas simulações em um sistema de distribuição de 20 kV.
2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018
The fusion of visible-light and infrared videos has applications in several areas, and is an acti... more The fusion of visible-light and infrared videos has applications in several areas, and is an active research topic. To this end, it is common to employ complex fusion methods that take into account spatial and/or temporal information in the videos. In this paper we propose a video fusion method that is based on a motion-compensated, two-band temporal sub-band decomposition. The alignment provided by the motion vectors, besides providing a reduction in the registration errors of the input images, allows the use of a simple fusion rule to the temporal sub-bands. The results indicate that the use of the proposed exploration of the temporal information alone is quite effective, and gives objective fusion quality results that compare favorably to more sophisticated methods based on complete spatiotemporal information.
IEEE Transactions on Circuits and Systems I: Regular Papers, 2021
Sign language is the main type of communication of the deaf community. However, most people do no... more Sign language is the main type of communication of the deaf community. However, most people do not know this language, which causes communication problems for many people. Many technological solutions have been proposed to overcome this issue. Some use the concept of wearable devices, but gesture recognition in a video sequence is a cheaper and less intrusive solution. In this work, we address the problem of gesture recognition in video. To do so, we employ a two-step method with feature space mapping and classification. First, the body parts of each subject in a video are segmented through a deep neural network architecture. Then, we use Gait Energy Image to encode the motion of the body parts in a compact feature space. Small datasets are usually a problem in this type of application, leading to sparse representation in the feature space. To contour this problem, we evaluate SMOTE as a data augmentation technique in the feature space and classical dimensionality reduction techniques. We evaluate our method on three challenging Brazilian sign language (Libras) datasets, CEFET/RJ-Libras, MINDS-Libras, and LIBRAS-UFOP, achieving global accuracies of 85.40±3.13%, 84.66±1.78%, and 64.91±3.79%, respectively, with singular value decomposition and support vector machine.
2020 Latin American Robotics Symposium (LARS), 2020 Brazilian Symposium on Robotics (SBR) and 2020 Workshop on Robotics in Education (WRE), 2020
Communication is a basic human necessity, but the deaf community is still facing some barriers. I... more Communication is a basic human necessity, but the deaf community is still facing some barriers. In Brazil, there are about 9.7 million people with some degree of hearing impairment but most Brazilians do not know the Brazilian Sign Language (Libras). Wearable gadgets like gloves or bracelets with sensors are a good tool to help in communication, but these solutions are pricey or intrusive. On the other hand, computer vision solutions are cheaper but challenging mainly due to the absence of reliable video databases. In this work, we propose a video database compounded by different signs, with various backgrounds, and different speakers. We also developed a system to perform computer vision-based sign recognition using the k-nearest neighbors (K-NN) and random forest (RF). In our tests, we achieved an average accuracy of 65.81 % in multiclass classification.
Anais do XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2021
Massive MIMO systems have received a growing interest since the apogee of 5G and the perspective ... more Massive MIMO systems have received a growing interest since the apogee of 5G and the perspective of 6G. Massive MIMO allows an efficient usage of spectral resources and provides higher data rates. When the number of antennas increases, the energy consumption and the hardware cost in the base station also increase. The high energy consumption and processing may be addressed through the selection of antennas. Among various possible structures in the literature, the present work proposes the combination of full-array architecture to make a virtual sectorization and antenna selection using matching pursuit. The algorithm was tested in different channels with complexity reduction in our tests while maintaining bit-error rate in most scenarios.
Anais do XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2021
In Brazil, there are around 10 million hard of hearing and deaf people. However, the majority of ... more In Brazil, there are around 10 million hard of hearing and deaf people. However, the majority of Brazilians are not fluent in the Brazilian Sign Language (Libras). Many members of the hearing impaired and deaf community have communication issues in everyday life situations. Technological solutions can aid in mitigating this problem. This work proposes a semi-supervised method to identify and classify signals in Libras from Youtube videos. The routine starts by segmenting the videos through a measure of movement intensity. We catalog the video segments according to the corresponding subtitles, which we extract by employing Optical Character Recognition (OCR) if embedded. It composes an ad-hoc dataset that we use to train a Libras recognition system. A Convolutional Neural Network (CNN) performs feature extraction frame-by-frame, and a Recurrent Neural Network (RNN) models the time correlation between the features, thus classifying the signal. The proposed method can achieve accuracy up to 61.6% in the ad-hoc dataset used in this work.
2021 IEEE 12th Latin America Symposium on Circuits and System (LASCAS), 2021
A common problem faced by the deaf community is that most people do not know sign language so com... more A common problem faced by the deaf community is that most people do not know sign language so communication is still an issue. This is not different in Brazil, where the sign language is called Libras. Many technological solutions are being proposed but gesture recognition in video sequences is the less intrusive one. In this work, we address the problem of recognizing gestures of Libras in video sequences. To do so, we first segment the body parts of the person in the video using a deep neural network architecture, in a frame by frame fashion. Then, we employ Gait Energy Image to encode the motion into a compact feature space. These features are fed to a classifier to attribute a label to each video. In our experiments, we achieved the 53.90±5.48% of accuracy using K-Nearest Neighbors and 79.57±2.39% using Random Forest in the best configuration across the 24 dataset classes.
2021 14th IEEE International Conference on Industry Applications (INDUSCON), 2021
The occurrence of high impedance faults (HIF) in primary distribution grid poses a danger to the ... more The occurrence of high impedance faults (HIF) in primary distribution grid poses a danger to the safety of people, equipment, and animals. However, protection devices along the distribution network are not capable of being sensitized by this type of defect, most of the time. This work presents an integrated strategy of HIF classification and detection, based on the use of Support Vector Machines. An improved fault model was used to emulate randomness behaviors, and especially intermittence of high impedance faults. The residual current is monitored, and the extraction of its characteristics is performed with Short-Time Fourier Transform. A logic of temporal consistency has been applied to the detection stage. The presented algorithm´s operation was achieved throughout several simulations in a 20 kV distribution system.
Multidimensional Systems and Signal Processing, 2017
In general, the fusion of visible-light and infrared images produces a composite representation w... more In general, the fusion of visible-light and infrared images produces a composite representation where both data are pictured in a single image. The successful development of image/video fusion algorithms relies on realistic infrared/visible-light datasets. To the best of our knowledge, there is a particular shortage of databases with registered and synchronized videos from the infrared and visible-light spectra suitable for image/video fusion research. To address this need we recorded an image/video fusion database using infrared and visible-light cameras under varying illumination conditions. Moreover, different scenarios have been defined to better challenge the fusion methods, with various contexts and contents providing a wide variety of meaningful data for fusion purposes, including nonplanar scenes, where objects appear on different depth planes. However, there are several difficulties in creating datasets for research in infrared/visible-light image fusion. Camera calibration, registration, and synchronization can be listed as important steps of this task. In particular, image registration between imagery from sensors of different spectral bands imposes additional difficulties, as it is very challenging to solve the correspondence problem between such images. Motivated by these challenges, this work introduces a novel spatiotemporal video registration method capable of generating registered and temporally aligned infrared/visible-light video sequences. The proposed workflow improves the registration ac
In this paper we investigate how visualization factors, such as disparity, mobility, angular reso... more In this paper we investigate how visualization factors, such as disparity, mobility, angular resolution and viewpoint interpolation, influence the Quality of Experience (QoE) in a stereoscopic multiview environment. In order to do so, we set up a dedicated testing room and conducted subjective experiments. We also developed a framework that emulates a super-multiview environment. This framework can be used to investigate and assess the effects of angular resolution and viewpoint interpolation on the quality of experience produced by multiview systems, and provide relevant cues as to how the baselines of cameras and interpolation strategies in such systems affect user experience. Aspects such as visual comfort, model fluidity, sense of immersion, and the 3D experience as a whole have been assessed for several test cases. Obtained results suggest that user experience in an motion parallax environment is not as critically influenced by configuration parameters such as disparity as initially thought. In addition, extensive subjective tests have indicated that while users are very sensitive to angular resolution in multiview 3D systems, this sensitivity tends not to be as critical when a user is performing a task that involves a great amount of interaction with the multiview content. These tests have also indicated that interpolating intermediate viewpoints can be effective in reducing the required view density without degrading the perceived QoE.
Journal of Communication and Information Systems, 2016
The increasing exploitation of natural resources under water, particularly in the sea, has ignite... more The increasing exploitation of natural resources under water, particularly in the sea, has ignited the development of many technological advances in the domains of environmental monitoring, oil and gas exploration, warfare, among others. In all these domains, underwater wireless communications play an important role, where the technologies available rely on radiofrequency, optical, and acoustic transmissions. This paper surveys key features inherent to these communication technologies, putting into perspective their technical aspects, current research challenges, and to-be-explored potential. I. INTRODUCTION Underwater wireless communications present new and distinct challenges when compared to wired and wireless communications through the atmosphere, requiring sophisticated communication devices to achieve relatively low transmission rates, even over short distances. Indeed, the underwater environment possesses a number of distinguishing features that make it unique and rather different from terrestrial radio propagation where traditional communication systems are deployed. Under water, several phenomena may influence communications, such as salt concentration, pressure, temperature, amount of light, winds and their effects on waves, just to mention a few [1], [2]. Despite all challenges, wireless communications certainly play an important role in practical underwater systems. Monitoring different phenomena in underwater environment is relevant in many different applications, such as oil and gas exploration, coastal security, environmental impact surveillance, navigation, and ocean-pollution control [3]. Specific examples include transmission of data among devices, such as AUV (autonomous underwater vehicle) to AUV and buoy to AUV, particularly those employing wireless links. In fact, an entire underwater wireless communication network could
Big data analytics, applied in the industry to leverage data collection, processing and analysis,... more Big data analytics, applied in the industry to leverage data collection, processing and analysis, can allow a better understanding of production system's abnormal behavior. This knowledge is essential for the adoption of a proactive maintenance approach instead of conventional time-based strategies, leading to a paradigm shift towards Condition-Based Maintenance (CBM) since decision is now based on the usage of a huge, diverse, and dynamic amounts of data as a means to optimize operational costs. This paper reports an investigation of the emerging aspects in the design and implementation of big data analytics solutions for offshore installations in order to allow predictive maintenance practices. Condition-based maintenance focuses on performing interventions based on the actual and future states (health) of a system by monitoring the underlying deterioration processes. One of the building blocks of a CBM design and implementation is the prognostic approach/system, which aims to...
2013 IEEE International Conference on Image Processing, 2013
The accurate geometric calibration of thermal infrared (IR) cameras is of vital importance in man... more The accurate geometric calibration of thermal infrared (IR) cameras is of vital importance in many computer vision applications. In general, the calibration procedure consists of localizing a set of calibration points within a calibration image. This set is subsequently used to solve for the camera parameters. However, due to the physical limitations of the IR acquisition process, the localization of the calibration points often poses difficulties, subsequently leading to unsatisfying calibration results. In this work a novel IR camera calibration approach is introduced. It is able to localize the calibration points within the images of a conventional calibration board consisting of miniature light-bulbs with improved accuracy. Our algorithm models the radiation pattern of each light bulb as an ellipse and considers the center of mass of the extracted ellipsoidal region as the starting calibration point, which is refined iteratively using alternating mappings to and from an undistorted grid model. The proposed processing chain leads to a significantly reduced calibration error when compared to the state-of-the-art. Furthermore, the proposed methodology can also be used to calibrate visible-light cameras thus being suitable for the calibration of multiple camera rigs involving both visible-light and IR cameras.
In this work we investigate how the angular resolution of a camera system influences the user exp... more In this work we investigate how the angular resolution of a camera system influences the user experience in immersive, interactive 3D applications. In order to investigate that, we developed a parallax-based framework that renders 3D models and tracks the user position by detecting LEDs or infrared markers attached to 3D glasses. The presented framework allows to simulate a system with an arbitrary number of viewpoints by changing the resolution of the users' tracked position. Extensive subjective tests were conducted where users interacted with the 3D models while the number of available viewpoints (angular resolution) was changed.
Traditional temporal video alignment techniques depend on the existence of a sufficient number of... more Traditional temporal video alignment techniques depend on the existence of a sufficient number of mutual scene characteristics to perform temporal synchronization. However, for video sequences originating from different spectral modalities such information may fail to exist, subsequently leading to unreliable alignment results. In this work, a novel, practical approach for the temporal alignment of infrared (IR) and visiblelight video sequences is introduced. Utilizing a planar alignment device consisting of an array of miniature light bulbs, we propose to increase the number of mutual feature points within the frames of a temporally misaligned IR/visible-light video sequence pair. Thereby, we provide an abundant number of mutual scene characteristics which can subsequently be used to determine the time-shift between the two sequences. Tests with five different IR/visible-light sequence pairs suggest that our technique is able to estimate the temporal offset with a very high confidence level. Furthermore, due to the simplicity of the construction of the alignment board, the proposed framework can be seamlessly integrated within a stereo camera calibration scheme.
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