References of "Ottersten, Björn 50002797"
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See detailTowards Automatic Human Body Model Fitting to a 3D Scan
Saint, Alexandre Fabian A UL; Shabayek, Abd El Rahman UL; Aouada, Djamila UL et al

in D'APUZZO, Nicola (Ed.) Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Montreal QC, Canada, 11-12 Oct. 2017 (2017, October)

This paper presents a method to automatically recover a realistic and accurate body shape of a person wearing clothing from a 3D scan. Indeed, in many practical situations, people are scanned wearing ... [more ▼]

This paper presents a method to automatically recover a realistic and accurate body shape of a person wearing clothing from a 3D scan. Indeed, in many practical situations, people are scanned wearing clothing. The underlying body shape is thus partially or completely occluded. Yet, it is very desirable to recover the shape of a covered body as it provides non-invasive means of measuring and analysing it. This is particularly convenient for patients in medical applications, customers in a retail shop, as well as in security applications where suspicious objects under clothing are to be detected. To recover the body shape from the 3D scan of a person in any pose, a human body model is usually fitted to the scan. Current methods rely on the manual placement of markers on the body to identify anatomical locations and guide the pose fitting. The markers are either physically placed on the body before scanning or placed in software as a postprocessing step. Some other methods detect key points on the scan using 3D feature descriptors to automate the placement of markers. They usually require a large database of 3D scans. We propose to automatically estimate the body pose of a person from a 3D mesh acquired by standard 3D body scanners, with or without texture. To fit a human model to the scan, we use joint locations as anchors. These are detected from multiple 2D views using a conventional body joint detector working on images. In contrast to existing approaches, the proposed method is fully automatic, and takes advantage of the robustness of state-of-art 2D joint detectors. The proposed approach is validated on scans of people in different poses wearing garments of various thicknesses and on scans of one person in multiple poses with known ground truth wearing close-fitting clothing. [less ▲]

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See detailRelay Selection Strategies for SWIPT-Enabled Cooperative Wireless Systems
Gautam, Sumit UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Montreal, Canada, Oct. 2017 (2017, October)

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See detailComputationally Efficient Symbol-Level Precoding Communications Demonstrator
Merlano Duncan, Juan Carlos UL; Krivochiza, Jevgenij UL; Andrenacci, Stefano UL et al

in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (2017, October)

We present a precoded multi-user communication test-bed to demonstrate forward link interference mitigation techniques in a multi-beam satellite system scenario which will enable a full frequency reuse ... [more ▼]

We present a precoded multi-user communication test-bed to demonstrate forward link interference mitigation techniques in a multi-beam satellite system scenario which will enable a full frequency reuse scheme. The developed test-bed provides an end-to-end precoding demonstration, which includes a transmitter, a multi-beam satellite channel emulator and user receivers. Each of these parts can be reconfigured accordingly to the desired test scenario. Precoded communications allow full frequency reuse in multiple-input multiple-output (MIMO) channel environments, where several coordinated antennas simultaneously transmit to a number of independent receivers. The developed real-time transmission test-bed assist in demonstrating, designing and benchmarking of the new Symbol-Level Precoding (SLP) techniques, where the data information is used, along with the channel state information, in order to exploit the multi-user interference and transform it into useful power at the receiver side. The demonstrated SLP techniques are designed in order to be computationally efficient, and can be generalized to others multi-channel interference scenarios. [less ▲]

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See detailFacial Expression Recognition via Joint Deep Learning of RGB-Depth Map Latent Representations
Oyedotun, Oyebade UL; Demisse, Girum UL; Shabayek, Abd El Rahman UL et al

in 2017 IEEE International Conference on Computer Vision Workshop (ICCVW) (2017, August 21)

Humans use facial expressions successfully for conveying their emotional states. However, replicating such success in the human-computer interaction domain is an active research problem. In this paper, we ... [more ▼]

Humans use facial expressions successfully for conveying their emotional states. However, replicating such success in the human-computer interaction domain is an active research problem. In this paper, we propose deep convolutional neural network (DCNN) for joint learning of robust facial expression features from fused RGB and depth map latent representations. We posit that learning jointly from both modalities result in a more robust classifier for facial expression recognition (FER) as opposed to learning from either of the modalities independently. Particularly, we construct a learning pipeline that allows us to learn several hierarchical levels of feature representations and then perform the fusion of RGB and depth map latent representations for joint learning of facial expressions. Our experimental results on the BU-3DFE dataset validate the proposed fusion approach, as a model learned from the joint modalities outperforms models learned from either of the modalities. [less ▲]

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See detailRandom Phase Center Motion Technique for Enhanced Angle-Doppler Discrimination Using MIMO Radars
Hammes, Christian UL; Shankar, Bhavani UL; Nijsure, Yogesh UL et al

in European Signal Processing Conference (EUSIPCO) 2017 (2017, August)

A random Phase Center Motion (PCM) technique is presented in this paper, based on Frequency Modulated Continuous Wave (FMCW) radar, in order to suppress the angle- Doppler coupling in Time Division ... [more ▼]

A random Phase Center Motion (PCM) technique is presented in this paper, based on Frequency Modulated Continuous Wave (FMCW) radar, in order to suppress the angle- Doppler coupling in Time Division Multiplex (TDM) Multiple- Input-Multiple-Output (MIMO) radar when employing sparse array structures. The presented approach exploits an apparently moving transmit platform or PCM due to spatio-temporal transmit array modulation. In particular, the work considers a framework utilizing a random PCM trajectory. The statistical characterization of the random PCM trajectory is devised, such that the PCM and the target motion coupling is minimal, while the angular resolution is increased by enabling the virtual MIMO concept. In more details, this paper discusses sidelobe suppression approaches within the angle-Doppler Ambiguity Function (AF) by introducing a phase center probability density function within the array. This allows for enhanced discrimination of multiple targets. Simulation results demonstrate the suppression angle- Doppler coupling by more than 30 dB, even though spatiotemporal transmit array modulation is done across chirps which leads usually to strong angle-Doppler coupling. [less ▲]

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See detailTraining Very Deep Networks via Residual Learning with Stochastic Input Shortcut Connections
Oyedotun, Oyebade UL; Shabayek, Abd El Rahman UL; Aouada, Djamila UL et al

in 24th International Conference on Neural Information Processing, Guangzhou, China, November 14–18, 2017 (2017, July 31)

Many works have posited the benefit of depth in deep networks. However, one of the problems encountered in the training of very deep networks is feature reuse; that is, features are ’diluted’ as they are ... [more ▼]

Many works have posited the benefit of depth in deep networks. However, one of the problems encountered in the training of very deep networks is feature reuse; that is, features are ’diluted’ as they are forward propagated through the model. Hence, later network layers receive less informative signals about the input data, consequently making training less effective. In this work, we address the problem of feature reuse by taking inspiration from an earlier work which employed residual learning for alleviating the problem of feature reuse. We propose a modification of residual learning for training very deep networks to realize improved generalization performance; for this, we allow stochastic shortcut connections of identity mappings from the input to hidden layers.We perform extensive experiments using the USPS and MNIST datasets. On the USPS dataset, we achieve an error rate of 2.69% without employing any form of data augmentation (or manipulation). On the MNIST dataset, we reach a comparable state-of-the-art error rate of 0.52%. Particularly, these results are achieved without employing any explicit regularization technique. [less ▲]

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See detailMulti-antenna based one-bit spatio-temporal wideband sensing for cognitive radio networks
Merlano Duncan, Juan Carlos UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in Proceedings of IEEE International Conference on Communications (ICC) 2017 (2017, July 31)

Cognitive Radio (CR) communication has been considered as one of the promising technologies to enable dynamic spectrum sharing in the next generation of wireless networks. Among several possible enabling ... [more ▼]

Cognitive Radio (CR) communication has been considered as one of the promising technologies to enable dynamic spectrum sharing in the next generation of wireless networks. Among several possible enabling techniques, Spectrum Sensing (SS) is one of the key aspects for enabling opportunistic spectrum access in CR Networks (CRN). From practical perspectives, it is important to design low-complexity wideband CR receiver having low resolution Analog to Digital Converter (ADC) working at a reasonable sampling rate. In this context, this paper proposes a novel spatio-temporal wideband SS technique by employing multiple antennas and one-bit quantization at the CR node, which subsequently enables the use of a reasonable sampling rate. In our analysis, we show that for the same sensing performance requirements, the proposed wideband receiver can have lower power consumption than the conventional CR receiver equipped with a single-antenna and a high-resolution ADC. Furthermore, the proposed technique exploits the spatial dimension by estimating the direction of arrival of Primary User (PU) signals, which is not possible by the conventional SS methods and can be of a significant benefit in a CRN. Moreover, we evaluate the performance of the proposed technique and analyze the effects of one-bit quantization with the help of numerical results. [less ▲]

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See detailPower Allocation for In-Band Full-Duplex Self-Backhauling
Lagunas, Eva UL; Lei, Lei UL; Maleki, Sina UL et al

in International Conference on Telecommunications and Signal Processing (TSP), Barcelona, Spain, July 2017 (2017, July)

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See detailSpatial PAPR Reduction in Symbol-level Precoding for the Multi-beam Satellite Downlink
Spano, Danilo UL; Alodeh, Maha UL; Chatzinotas, Symeon UL et al

in IEEE SPAWC 2017 (2017, July)

In this work, a novel symbol-level precoding scheme is proposed, for managing the multi-user interference in the forward downlink channel of a multi-beam satellite system. Besides exploiting the ... [more ▼]

In this work, a novel symbol-level precoding scheme is proposed, for managing the multi-user interference in the forward downlink channel of a multi-beam satellite system. Besides exploiting the constructive interference effect, the proposed scheme aims at improving the robustness of the transmitted signals to the non-linear distortions of practical satellite systems. This is done by reducing the imbalances between the instantaneous power transmitted by the multiple antennas, which are detrimental in non-linear systems. More specifically, this work proposes a symbol-level precoding scheme performing the minimization of the spatial peak-to-average power ratio, under Quality-of-Service constraints. An iterative algorithm is proposed to solve the related optimization problem. Numerical results are presented to assess the performance of the proposed scheme, which outperforms the state of the art symbol-level precoding techniques in terms of spatial peak-to-average power ratio across the transmitting antennas. [less ▲]

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See detailEnergy-Efficient Design for Edge-caching Wireless Networks: When is Coded-caching beneficial?
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Proceedings of IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (2017, July)

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See detailInterference Constraint Active Learning with Uncertain Feedback for Cognitive Radio Networks
Tsakmalis, Anestis UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Wireless Communications (2017), 16(7), 4654-4668

In this paper, an intelligent probing method for interference constraint learning is proposed to allow a centralized cognitive radio network (CRN) to access the frequency band of a primary user (PU) in an ... [more ▼]

In this paper, an intelligent probing method for interference constraint learning is proposed to allow a centralized cognitive radio network (CRN) to access the frequency band of a primary user (PU) in an underlay cognitive communication scenario. The main idea is that the CRN probes the PU and subsequently eavesdrops the reverse PU link to acquire the binary ACK/NACK packet. This feedback is implicit channel state information of the PU link, indicating whether the probinginduced interference is harmful or not. The intelligence of this sequential probing process lies in the selection of the power levels of the secondary users, which aims to minimize the number of probing attempts, a clearly active learning (AL) procedure, and expectantly the overall PU QoS degradation. The enhancement introduced in this paper is that we incorporate the probability of each feedback being correct into this intelligent probing mechanism by using a multivariate Bayesian AL method. This technique is inspired by the probabilistic bisection algorithm and the deterministic cutting plane methods (CPMs). The optimality of this multivariate Bayesian AL method is proven and its effectiveness is demonstrated through numerical simulations. Computationally cheap CPM adaptations are also presented, which outperform existing AL methods. [less ▲]

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See detailLow Complexity Symbol-Level Design for Linear Precoding Systems
Krivochiza, Jevgenij UL; Kalantari, Ashkan UL; Chatzinotas, Symeon UL et al

in Heusdens, Richard; Weber, Jos H. (Eds.) PROCEEDINGS of the 2017 Symposium on Information Theory and Signal Processing in the Benelux (2017, May 11)

The practical utilization of the symbol-level precoding in MIMO systems is challenging since the implementation of the sophisticated optimization algorithms must be done with reasonable computational ... [more ▼]

The practical utilization of the symbol-level precoding in MIMO systems is challenging since the implementation of the sophisticated optimization algorithms must be done with reasonable computational resources. In the real implementation of MIMO precoding systems, the processing time for each set of symbols is a crucial parameter, especially in the high-throughput mode. In this work, a symbol-level optimization algorithm with reduced complexity is devised. Performance of a symbol-level precoder is shown to improve in terms of the processing times per set of symbols. [less ▲]

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See detailFinite-SNR analysis for partial relaying cooperation with channel coding and opportunistic relay selection
Vu, Thang Xuan UL; Duhamel, Pierre; Chatzinotas, Symeon UL et al

in EURASIP Journal on Advances in Signal Processing (2017)

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See detailSpectral-Efficient Model for Multiuser Massive MIMO: Exploiting User Velocity
Vu, Thang Xuan UL; Trinh, Anh Vu; Chatzinotas, Symeon UL et al

in IEEE international Conference on Communications (2017, May)

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See detailCarrier Allocation for Hybrid Satellite-Terrestrial Backhaul Networks
Lagunas, Eva UL; Maleki, Sina UL; Lei, Lei UL et al

in ICC Workshop on Satellite Communications: Challenges and Integration in the 5G ecosystem, Paris, France, May 2017 (2017, May)

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See detailDiscrimination of Angle-Doppler Signatures using Arbitrary Phase Center Motion for MIMO Radars
Hammes, Christian UL; Nijsure, Yogesh UL; Shankar, Bhavani UL et al

in IEEE Radar Conf 2017 (2017, May)

A novel Phase Center Motion (PCM) based technique for discriminating angle-Doppler signatures within Multiple-Input-Multiple-Output (MIMO) radars using Frequency Modulated Continuous Wave (FMCW) has been ... [more ▼]

A novel Phase Center Motion (PCM) based technique for discriminating angle-Doppler signatures within Multiple-Input-Multiple-Output (MIMO) radars using Frequency Modulated Continuous Wave (FMCW) has been explored in this work. The PCM technique induces angle dependent Doppler shifts in the back-scattered signal, wherein a modified Doppler post processing for FMCW leads to joint angle-Doppler processing. Specifically, we intend to design unique spatialtemporal motion of the phase center on each individual MIMO radar channel in an effort to synthesize nearly orthogonal angle-Doppler signatures. Subsequently, we also develop a MIMO radar receiver design, which would be capable of discriminating between these induced angle-Doppler signatures. The asymptotic investigation provides a Bessel function characteristic. Simulation results demonstrate a significant side-lobe suppression of 8:5 dB for an individual PCM trajectory and 7 dB over distinct PCM trajectories, in an attempt towards realization of nearly orthogonal MIMO radar channels. [less ▲]

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See detailOn the Diversity of Partial Relaying Cooperation with Relay Selection in Finite-SNR Regime
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE International Conference on Communications (2017, May)

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See detailFaster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels
Alodeh, Maha UL; Spano, Danilo UL; Chatzinotas, Symeon UL et al

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

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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 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 ▲]

Detailed reference viewed: 334 (66 UL)