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Detecting pedestrians is a challenging problem owing to the motion of the subjects, the camera and the background and to variations in pose, appearance, clothing, illumination and background clutter. The Region Covariance Matrix (RCM) descriptors show experimentally significantly out-performs existing feature sets for pedestrian detection. In this paper, we present an efficient features extraction...
The desire to improve short-term predictions of wind speed and direction has motivated the development of a spatial covariance-based predictor in a complex valued multichannel structure. Wind speed and direction are modelled as the magnitude and phase of complex time series and measurements from multiple geographic locations are embedded in a complex vector which is then used as input to a multichannel...
We use the Gaussian information bottleneck (GIB) to investigate the optimal rate-information trade-off for signal compression in linear Gaussian models and we provide a novel interpretation of the GIB in terms of the eigendecomposition of the Wiener filter. We further study mean-square-error-optimal rate-distortion compression preceded by a linear filter. Choosing this filter as square root of the...
A two-stage predictor strategy is introduced in the context of high dimensional data (large p, small n). Here the focus application is a medical one: prediction of symptomatic infection given molecular expression levels in blood. The first stage of the two-stage predictor uses the previously introduced method of Predictive Correlation Screening (PCS) to select a subset of genes that are important...
This work studies the performance of position estimation for distress beacons using time of arrival and frequency of arrival measurements. The analysis is conducted for emergency signals modeled as pulses with sigmoidal transitions. This model has shown interesting properties for Cospas-Sarsat search and rescue signals. The modified Cramér-Rao bounds of the symbol width, time of arrival, frequency...
Linear precoding for cooperative multi-cell transmission can provide substantial gains in user throughput, while channel state information (CSI) need to be available at the transmitter. Performance degradation due to imperfect CSI can be partially compensated by robust precoding techniques. For distributed precoding the pre-processing of the user data is performed locally at each base station (BS),...
We explore the problem of anomaly detection based on several one-dimensional projections. The main advantage of the proposed approach is that it does not require any covariance matrix estimation, allowing to compute spatial adaptive anomaly detection in small neighborhoods. Although this is contrary to common sense, theoretical results support the consistence of our approach when a large number of...
This paper presents an efficient extended Kalman filter implementation of a single-camera visual simulataneous localization and mapping (vSLAM) algorithm, vSLAM is a novel algorithm for simultaneous localization and mapping problem widely studied in mobile robotics field. The algorithm is vision and odometry-based. The problem with the implementation of all SLAM algorithms is the state vector size...
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