Conference Papers by Björn Ottersten
IEEE International Conference on Image Processing (ICIP), Oct 2010
This paper introduces a new multi-lateral filter to fuse low-resolution depth maps with high-reso... more This paper introduces a new multi-lateral filter to fuse low-resolution depth maps with high-resolution images. The goal is to enhance the resolution of Time-of-Flight sensors and, at the same time, reduce the noise level in depth measurements. Our approach is based on the joint bilateral upsampling, extended by a new factor that considers the low reliability of depth measurements along the low-resolution depth map edges. Our experimental results show better performances than alternative depth enhancing data fusion techniques.
International Conference on Computer Vision Theory and Applications (VISAPP), Mar 2015
This paper presents a practical and robust approach for upright human curve-skeleton extraction. ... more This paper presents a practical and robust approach for upright human curve-skeleton extraction. Curve-skeletons are object descriptors that represent a simplified version of the geometry and topology of a 3-D object. The curve-skeleton of a human-scanned point set enables the approximation of the underlying skeletal structure and thus, to estimate the body configuration (human pose). In contrast to most curve-skeleton extraction methodologies from the literature, we herein propose a real-time curve-skeleton extraction approach that applies to scanned point clouds, independently of the object's complexity and/or the amount of noise within the depth measurements. The experimental results show the ability of the algorithm to extract a centered curve-skeleton within the 3-D object, with the same topology, and with unit thickness. The proposed approach is intended for real world applications and hence, it handles large portions of data missing due to occlusions, acquisition hindrances or registration inaccuracies.
Papers by Björn Ottersten
Low complexity asynchronous DS-CDMA detectors
Proceedings of Vehicular Technology Conference - VTC, 1996
Near-far resistant multiuser-detectors for an asynchronous direct-sequence code-division multiple... more Near-far resistant multiuser-detectors for an asynchronous direct-sequence code-division multiple access (DS-CDMA) system, which do not need the code-matched filter outputs from all users are presented. Two complex-valued, discrete-time vector models for the system are formulated. Detectors for both models, that work on blocks of data of M symbols are considered. The problem of estimation of the bits is posed in a least squares sense and as a minimum mean squared error problem. The performance of the detection algorithms is investigated by computing the BER (bit error rate) on simulated data. Comparisons with traditional detectors is also carried out. It is shown that detectors based on the compact vector model performs slightly worse than detectors based on the more complex vector model
Bilateral filter evaluation based on exponential kernels
Proceedings of the 21st International Conference on Pattern Recognition, Nov 1, 2012
ABSTRACT The well-known bilateral filter is used to smooth noisy images while keeping their edges... more ABSTRACT The well-known bilateral filter is used to smooth noisy images while keeping their edges. This filter is commonly used with Gaussian kernel functions without real justification. The choice of the kernel functions has a major effect on the filter behavior. We propose to use exponential kernels with L1 distances instead of Gaussian ones. We derive Stein's Unbiased Risk Estimate to find the optimal parameters of the new filter and compare its performance with the conventional one. We show that this new choice of the kernels has a comparable smoothing effect but with sharper edges due to the faster, smoothly decaying kernels.
Low Complexity Estimation of Angular Spread with an Antenna Array
ABSTRACT
Maximum likelihood based sparse and distributed conjoint analysis
2012 Ieee Statistical Signal Processing Workshop, 2012
ABSTRACT A new statistical model for choice-based conjoint analysis is proposed. The model uses a... more ABSTRACT A new statistical model for choice-based conjoint analysis is proposed. The model uses auxiliary variables to account for outliers and to detect the salient features that influence decisions. Unlike recent classification-based approaches to choice-based conjoint analysis, a sparsity-aware maximum likelihood (ML) formulation is proposed to estimate the model parameters. The proposed approach is conceptually appealing, mathematically tractable, and is also well-suited for distributed implementation. Its performance is tested and compared to the prior state-of-art using synthetic as well as real data coming from a conjoint choice experiment for coffee makers, with very promising results.
Channel Dependent Termination of the
Ieee Signal Processing Letters, Oct 1, 2014
We consider the problem of estimating a deterministic unknown vector which depends linearly on no... more We consider the problem of estimating a deterministic unknown vector which depends linearly on noisy measurements, additionally contaminated with (possibly unbounded) additive outliers. The measurement matrix of the model (i.e., the matrix involved in the linear transformation of the sought vector) is assumed known, and comprised of standard Gaussian i.i.d. entries. The outlier variables are assumed independent of the measurement matrix, deterministic or random with possibly unknown distribution. Under these assumptions we provide a simple proof that the minimizer of the Huber penalty function of the residuals converges to the true parameter vector with a -rate, even when outliers are dense, in the sense that there is a constant linear fraction of contaminated measurements which can be arbitrarily close to one. The constants influencing the rate of convergence are shown to explicitly depend on the outlier contamination level.
Sector Array Mapping : Transformation Matrix Design for Minimum MSE
ABSTRACT
Ieee Transactions on Signal Processing, Jun 29, 2014
A multi-antenna transmitter that conveys independent sets of common data to distinct groups of us... more A multi-antenna transmitter that conveys independent sets of common data to distinct groups of users is considered. This model is known as physical layer multicasting to multiple co-channel groups. In this context, the practical constraint of a maximum permitted power level radiated by each antenna is addressed. The per-antenna power constrained system is optimized in a maximum fairness sense with respect to predetermined quality of service weights. In other words, the worst scaled user is boosted by maximizing its weighted signal-to-interference plus noise ratio. A detailed solution to tackle the weighted max-min fair multigroup multicast problem under per-antenna power constraints is therefore derived. The implications of the novel constraints are investigated via prominent applications and paradigms. What is more, robust per-antenna constrained multigroup multicast beamforming solutions are proposed. Finally, an extensive performance evaluation quantifies the gains of the proposed algorithm over existing solutions and exhibits its accuracy over per-antenna power constrained systems.
In this work we propose KinectDeform, an algorithm which targets enhanced 3D reconstruction of sc... more In this work we propose KinectDeform, an algorithm which targets enhanced 3D reconstruction of scenes containing non-rigidly deforming objects. It provides an innovation to the existing class of algorithms which either target scenes with rigid objects only or allow for very limited non-rigid deformations or use precomputed templates to track them. KinectDeform combines a fast non-rigid scene tracking algorithm based on octree data representation and hierarchical voxel associations with a recursive data filtering mechanism. We analyze its performance on both real and simulated data and show improved results in terms of smoothness and feature preserving 3D reconstructions with reduced noise.
We highlight some recent results on the theory and algorithms for MIMO systems, obtained at the R... more We highlight some recent results on the theory and algorithms for MIMO systems, obtained at the Royal Institute of Technology (KTH) within the SATURN project. The paper includes a a new approximate expression for the ergodic channel capacity of a MIMO system with correlated fading, algorithms for MIMO beamforming under EIRP (equivalent isotropic radiated power) constraints and a low-complexity algorithm for MIMO channel estimation in OFDM systems. Also, we show how transmit and beamformers can be determined in a decentralized fashion without explicitly estimating the channel response. * This report is a part of the work done within the IST-SATURN project.
A statistical approach to subspace based estimation with applications in telecommunications
Proceedings of the Second International Workshop on Recent Advances in Total Least Squares Techniques and Errors in Variables Modeling, Oct 1, 1997
ABSTRACT Subspace based estimation using decomposition techniques such as the SVD is a powerful t... more ABSTRACT Subspace based estimation using decomposition techniques such as the SVD is a powerful tool in many signal processing applications where low rank signals in noise are observed. Examples of which include, sensor array signal processing, harmonic analysis, factor analysis, system identification, and blind channel equalization. By appropriately making use of eigenvalue or singular value decompositions, low rank approximations of the data may be obtained. From these approximations, subspace based, computationally efficient estimation techniques may be formulated. Also, the performance of subspace based methods is in many cases optimal or near optimal. This paper presents a systematic approach for formulating subspace based estimation techniques based on statistical considerations of the data. This approach may be applied to a wide range of problems where low rank signals are observed in noise. Some special cases are shown to result in well known estimators and examples of subspace based te...
The well-known bilateral filter is used to smooth noisy images while keeping their edges. This fi... more The well-known bilateral filter is used to smooth noisy images while keeping their edges. This filter is commonly used with Gaussian kernel functions without real justification. The choice of the kernel functions has a major effect on the filter behavior. We propose to use exponential kernels with L 1 distances instead of Gaussian ones. We derive Stein's Unbiased Risk Estimate to find the optimal parameters of the new filter and compare its performance with the conventional one. We show that this new choice of the kernels has a comparable smoothing effect but with sharper edges due to the faster, smoothly decaying kernels.
Transmit Diversity with Interference Suppression in EDGE
ABSTRACT
On Approximating a Spatially Scattered Source with Two Point Sources
Simple spatial multiplexing based on imperfect channel estimates
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004
Techniques for communication over flat multi-input, multi-output (MIMO) channels are well establi... more Techniques for communication over flat multi-input, multi-output (MIMO) channels are well established when either perfect channel state information or no channel state information is available at the transmitter. However, communication over channels where the transmitter has access to partial or imperfect information has received less attention. If exploited, such information could improve system performance. We propose a simple system design scheme, that approximately maximizes the data rates of MIMO communication systems where imperfect channel estimates are available at the transmitter. The algorithm is computationally attractive and, by taking the uncertainty of the channel estimates into account in the design, gains can be demonstrated compared with systems not exploiting this information.
Experiments Using an Antenna Array in a Mobile Communications Environment
IEEE Seventh SP Workshop on Statistical Signal and Array Processing, 1994
ABSTRACT
In the design of next generation multiuser communication systems, multiple antenna transmission i... more In the design of next generation multiuser communication systems, multiple antenna transmission is an essential part providing spatial multiplexing gain and allowing efficient use of resources. A major limiting factor in the resource allocation is the amount of channel state information (CSI) available at the transmitter, particularly in multiuser systems where the feedback from each user terminal must be limited.
GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270), 2001
Herein, results from measurements conducted by the University of Bristol are presented. The chann... more Herein, results from measurements conducted by the University of Bristol are presented. The channel characteristics of Multiple Input Multiple Output (MIMO) indoor systems at 5.2 GHz are studied. Our investigation shows that the envelope of the channel for non-line-of-sight (NLOS) indoor situations are approximately Rayleigh distributed and consequently we focus on a statistical description of the first and second order moments of the narrowband MIMO channel. Furthermore, it is shown that for NLOS indoor scenarios, the MIMO channel covariance matrix can be well approximated by a Kronecker product of the covariance matrices describing the correlation at the transmitter and receiver side respectively. A statistical narrowband model for the NLOS indoor MIMO channel based on this covariance structure is presented. 156 0-7803-7206-9/01/$17.00
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Conference Papers by Björn Ottersten
Papers by Björn Ottersten