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See detailVideo-Based Feedback for Assisting Physical Activity
Baptista, Renato UL; Goncalves Almeida Antunes, Michel UL; Aouada, Djamila UL et al

in 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) (2017)

In this paper, we explore the concept of providing feedback to a user moving in front of a depth camera so that he is able to replicate a specific template action. This can be used as a home based ... [more ▼]

In this paper, we explore the concept of providing feedback to a user moving in front of a depth camera so that he is able to replicate a specific template action. This can be used as a home based rehabilitation system for stroke survivors, where the objective is for patients to practice and improve their daily life activities. Patients are guided in how to correctly perform an action by following feedback proposals. These proposals are presented in a human interpretable way. In order to align an action that was performed with the template action, we explore two different approaches, namely, Subsequence Dynamic Time Warping and Temporal Commonality Discovery. The first method aims to find the temporal alignment and the second one discovers the interval of the subsequence that shares similar content, after which standard Dynamic Time Warping can be used for the temporal alignment. Then, feedback proposals can be provided in order to correct the user with respect to the template action. Experimental results show that both methods have similar accuracy rate and the computational time is a decisive factor, where Subsequence Dynamic Time Warping achieves faster results. [less ▲]

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See detailEnhanced Trajectory-based Action Recognition using Human Pose
Papadopoulos, Konstantinos UL; Goncalves Almeida Antunes, Michel UL; Aouada, Djamila UL et al

in IEEE International Conference on Image Processing, Beijing 17-20 Spetember 2017 (2017)

Action recognition using dense trajectories is a popular concept. However, many spatio-temporal characteristics of the trajectories are lost in the final video representation when using a single Bag-of ... [more ▼]

Action recognition using dense trajectories is a popular concept. However, many spatio-temporal characteristics of the trajectories are lost in the final video representation when using a single Bag-of-Words model. Also, there is a significant amount of extracted trajectory features that are actually irrelevant to the activity being analyzed, which can considerably degrade the recognition performance. In this paper, we propose a human-tailored trajectory extraction scheme, in which trajectories are clustered using information from the human pose. Two configurations are considered; first, when exact skeleton joint positions are provided, and second, when only an estimate thereof is available. In both cases, the proposed method is further strengthened by using the concept of local Bag-of-Words, where a specific codebook is generated for each skeleton joint group. This has the advantage of adding spatial human pose awareness in the video representation, effectively increasing its discriminative power. We experimentally compare the proposed method with the standard dense trajectories approach on two challenging datasets. [less ▲]

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See detailDEFORMATION TRANSFER OF 3D HUMAN SHAPES AND POSES ON MANIFOLDS
Shabayek, Abd El Rahman UL; Aouada, Djamila UL; Saint, Alexandre Fabian A UL et al

in IEEE International Conference on Image Processing, Beijing 17-20 Spetember 2017 (2017)

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See detailCoded Caching and Storage Planning in Heterogeneous Networks
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in 2017 IEEE Wireless Communications and Networking Conference (WCNC) (2017)

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See detailSymbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Alodeh, Maha UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Wireless Communications (2017)

Symbol-level precoding is a new paradigm for multiuser multiple-antenna downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by ... [more ▼]

Symbol-level precoding is a new paradigm for multiuser multiple-antenna downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for Mary phase shift keying (MPSK) modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. Mary quadrature amplitude modulation (MQAM) by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user signal to interference noise ratio (SINR) or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate. [less ▲]

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See detailOn the Energy-Efficiency of Hybrid Analog-Digital Transceivers for Single- and Multi-carrier Large Antenna Array Systems
Tsinos, Christos UL; Maleki, Sina UL; Chatzinotas, Symeon UL et al

in IEEE Journal on Selected Areas In Communications (2017)

Hybrid Analog-Digital transceivers are employed with the view to reduce the hardware complexity and the energy consumption in millimeter wave/large antenna array systems by reducing the number of their ... [more ▼]

Hybrid Analog-Digital transceivers are employed with the view to reduce the hardware complexity and the energy consumption in millimeter wave/large antenna array systems by reducing the number of their Radio Frequency (RF) chains. However, the analog processing network requires power for its operation and it further introduces power losses, dependent on the number of the transceiver antennas and RF chains, that have to be compensated. Thus, the reduction in the power consumption is usually much less than it is expected and given that the hybrid solutions present in general inferior spectral efficiency than a fully digital one, it is possible for the former to be less energy efficient than the latter in several cases. Existing approaches propose hybrid solutions that maximize the spectral efficiency of the system without providing any insight on their energy requirements/efficiency. To that end, in this paper, a novel algorithmic framework is developed based on which energy efficient hybrid transceiver designs are derived and their performance is examined with respect to the number of RF chains and antennas. Solutions are proposed for fully and partially connected hybrid architectures and for both single- and multi-carrier systems under the Orthogonal Frequency Division Multiplexing (OFDM) modulation. Simulations and theoretical results provide insight on the cases where a hybrid transceiver is the most energy efficient solution or not. [less ▲]

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See detailOn the energy-efficiency of hybrid analog-digital transceivers for large antenna array systems
Tsinos, Christos UL; Maleki, Sina UL; Chatzinotas, Symeon UL et al

in On the energy-efficiency of hybrid analog-digital transceivers for large antenna array systems (2017)

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See detailDeformation Based Curved Shape Representation
Demisse, Girum UL; Aouada, Djamila UL; Ottersten, Björn UL

in IEEE Transactions on Pattern Analysis and Machine Intelligence (2017)

In this paper, we introduce a deformation based representation space for curved shapes in Rn. Given an ordered set of points sampled from a curved shape, the proposed method represents the set as an ... [more ▼]

In this paper, we introduce a deformation based representation space for curved shapes in Rn. Given an ordered set of points sampled from a curved shape, the proposed method represents the set as an element of a finite dimensional matrix Lie group. Variation due to scale and location are filtered in a preprocessing stage, while shapes that vary only in rotation are identified by an equivalence relationship. The use of a finite dimensional matrix Lie group leads to a similarity metric with an explicit geodesic solution. Subsequently, we discuss some of the properties of the metric and its relationship with a deformation by least action. Furthermore, invariance to reparametrization or estimation of point correspondence between shapes is formulated as an estimation of sampling function. Thereafter, two possible approaches are presented to solve the point correspondence estimation problem. Finally, we propose an adaptation of k-means clustering for shape analysis in the proposed representation space. Experimental results show that the proposed representation is robust to uninformative cues, e.g. local shape perturbation and displacement. In comparison to state of the art methods, it achieves a high precision on the Swedish and the Flavia leaf datasets and a comparable result on MPEG-7, Kimia99 and Kimia216 datasets. [less ▲]

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See detailMulti-Target Localization in Asynchronous MIMO Radars Using Sparse Sensing
Sedighi, Saeid UL; Shankar, Bhavani UL; Maleki, Sina UL et al

in IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) (2017)

Multi-target localization, warranted in emerging applications like autonomous driving, requires targets to be perfectly detected in the distributed nodes with accurate range measurements. This implies ... [more ▼]

Multi-target localization, warranted in emerging applications like autonomous driving, requires targets to be perfectly detected in the distributed nodes with accurate range measurements. This implies that high range resolution is crucial in distributed localization in the considered scenario. This work proposes a new framework for multi-target localization, addressing the demand for the high range resolution in automotive applications without increasing the required bandwidth. In particular, it employs sparse stepped frequency waveform and infers the target ranges by exploiting sparsity in target scene. The range measurements are then sent to a fusion center where direction of arrival estimation is undertaken. Numerical results illustrate the impact of range resolution on multi-target localization and the performance improvement arising from the proposed algorithm in such scenarios. [less ▲]

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See detailWeak Interference Detection with Signal Cancellation in Satellite Communications
Politis, Christos UL; Maleki, Sina UL; Tsinos, Christos UL et al

in The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2017 (2017)

Interference is identified as a critical issue for satellite communication (SATCOM) systems and services. There is a growing concern in the satellite industry to manage and mitigate interference ... [more ▼]

Interference is identified as a critical issue for satellite communication (SATCOM) systems and services. There is a growing concern in the satellite industry to manage and mitigate interference efficiently. While there are efficient techniques to monitor strong interference in SATCOM, weak interference is not so easily detected because of its low interference to signal and noise ratio (ISNR). To address this issue, this paper proposes and develops a technique which takes place on-board the satellite by decoding the desired signal, removing it from the total received signal and applying an Energy Detector (ED) in the remaining signal for the detection of interference. Different from the existing literature, this paper considers imperfect signal cancellation, examining how the decoding errors affect the sensing performance, derives the expressions for the probability of false alarm and provides a set of simulations results, verifying the efficiency of the technique. [less ▲]

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See detailCentralized Rainfall Estimation using Carrier-to-Noise of Satellite Communication Links
Gharanjik, Ahmad UL; Shankar, Bhavani UL; Zimmer, Frank et al

in IEEE Journal on Selected Areas In Communications (2017)

In this paper, we present a centralized method for real-time rainfall estimation using carrier-to-noise power ratio (C/N) measurements from broadband satellite communication networks. The C/N data of both ... [more ▼]

In this paper, we present a centralized method for real-time rainfall estimation using carrier-to-noise power ratio (C/N) measurements from broadband satellite communication networks. The C/N data of both forward link and return link are collected by the gateway station from the user terminals in the broadband satellite communication network and stored in a database. The C/N for such Ka-band scenarios is impaired mainly by the rainfall. Using signal processing and machine learning techniques, we develop an algorithm for real-time rainfall estimation. Extracting relevant features from C/N, we use artificial neural network in order to distinguish the rain events from dry events. We then determine the signal attenuation corresponding to the rain events and examine an empirical relationship between rainfall rate and signal attenuation. Experimental results are promising and prove the high potential of satellite communication links for real environment monitoring, particularly rainfall estimation. [less ▲]

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See detailDynamic Spectrum Sharing in 5G Wireless Networks with Full-Duplex Technology: Recent Advances and Research Challenges
Sharma; Bogale; Le et al

in IEEE Communications Surveys and Tutorials (2017)

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See detailFlexible Feedback System for Posture Monitoring and Correction
Baptista, Renato UL; Antunes, Michel; Shabayek, Abd El Rahman UL et al

in IEEE International Conference on Image Information Processing (ICIIP) (2017)

In this paper, we propose a framework for guiding patients and/or users in how to correct their posture in real-time without requiring a physical or a direct intervention of a therapist or a sports ... [more ▼]

In this paper, we propose a framework for guiding patients and/or users in how to correct their posture in real-time without requiring a physical or a direct intervention of a therapist or a sports specialist. In order to support posture monitoring and correction, this paper presents a flexible system that continuously evaluates postural defects of the user. In case deviations from a correct posture are identified, then feedback information is provided in order to guide the user to converge to an appropriate and stable body condition. The core of the proposed approach is the analysis of the motion required for aligning body-parts with respect to postural constraints and pre-specified template skeleton poses. Experimental results in two scenarios (sitting and weight lifting) show the potential of the proposed framework. [less ▲]

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See detailUnsupervised Vanishing Point Detection and Camera Calibration from a Single Manhattan Image with Radial Distortion
Goncalves Almeida Antunes, Michel UL; Barreto, Joao P.; Aouada, Djamila UL et al

in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (2017)

The article concerns the automatic calibration of a camera with radial distortion from a single image. It is known that, under the mild assumption of square pixels and zero skew, lines in the scene ... [more ▼]

The article concerns the automatic calibration of a camera with radial distortion from a single image. It is known that, under the mild assumption of square pixels and zero skew, lines in the scene project into circles in the image, and three lines suffice to calibrate the camera up to an ambiguity between focal length and radial distortion. The calibration results highly depend on accurate circle estimation, which is hard to accomplish, because lines tend to project into short circular arcs. To overcome this problem, we show that, given a short circular arc edge, it is possible to robustly determine a line that goes through the center of the corresponding circle. These lines, henceforth called Lines of Circle Centres (LCCs), are used in a new method that detects sets of parallel lines and estimates the calibration parameters, including the center and amount of distortion, focal length, and camera orientation with respect to the Manhattan frame. Extensive experiments in both semi-synthetic and real images show that our algorithm outperforms state- of-the-art approaches in unsupervised calibration from a single image, while providing more information. [less ▲]

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See detailEnergy Optimization for Full-Duplex Self-Backhauled HetNet with Non-Orthogonal Multiple Access
Lei, Lei UL; Lagunas, Eva UL; Maleki, Sina UL et al

in International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Sapporo, Japan, July 2017 (2017)

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See detailSimultaneous Sensing and Transmission for Cognitive Radios with Imperfect Signal Cancellation
Politis, Christos UL; Maleki, Sina UL; Tsinos, Christos UL et al

in IEEE Transactions on Wireless Communications (2017)

In conventional cognitive radio systems, the secondary user employs a “listen-before-talk” paradigm, where it senses if the primary user is active or idle, before it decides to access the licensed ... [more ▼]

In conventional cognitive radio systems, the secondary user employs a “listen-before-talk” paradigm, where it senses if the primary user is active or idle, before it decides to access the licensed spectrum. However, this method faces challenges with the most important being the reduction of the secondary user’s throughput, as no data transmission takes place during the sensing period. In this context, the idea of simultaneous spectrum sensing and data transmission is proposed. The present work studies a system model where this concept is obtained through the collaboration of the secondary transmitter with the secondary receiver. First, the secondary receiver decodes the signal from the secondary transmitter, subsequently, removes it from the total received signal and then, carries out spectrum sensing in the remaining signal in order to decide about the presence/absence of the primary user. Different from the existing literature, this paper takes into account the imperfect signal cancellation, evaluating how the decoding errors affect the sensing reliability and derives the analytical expressions for the probability of false alarm. Finally, numerical results are presented illustrating the accuracy of the proposed analysis. [less ▲]

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See detailFraud Detection by Stacking Cost-Sensitive Decision Trees
Correa Bahnsen, Alejandro; Villegas, Sergio; Aouada, Djamila UL et al

in Data Science for Cyber-Security (DSCS), London 25-27 September (2017)

Detailed reference viewed: 219 (3 UL)
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See detailSpectral coexistence for next generation wireless backhaul networks
Sharma, Shree Krishna; Lagunas, Eva UL; Tsinos, Christos UL et al

in Access, Fronthaul and Backhaul Networks for 5G and Beyond (2017)

Detailed reference viewed: 137 (3 UL)
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See detailCodebook-Based Hybrid Precoding for Millimeter Wave Multiuser Systems
He, S.; Wang, J.; Huang, Y. et al

in IEEE Transactions on Signal Processing (2017), 65(20), 5289-5304

Detailed reference viewed: 144 (3 UL)