xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera

We present a new solution to egocentric 3D body pose estimation from monocular images captured from a downward looking fish-eye camera installed on the rim of a head mounted virtual reality device. This unusual viewpoint, just 2 cm away from the user's face, leads to images with unique visual appearance, characterized by severe self-occlusions and strong perspective distortions that result in a drastic difference in resolution between lower and upper body. Our contribution is two-fold. Firstly, we propose a new encoder-decoder architecture with a novel dual branch decoder designed specifically to account for the varying uncertainty in the 2D joint locations. Our quantitative evaluation, both on synthetic and real-world datasets, shows that our strategy leads to substantial improvements in accuracy over state of the art egocentric pose estimation approaches. Our second contribution is a new large-scale photorealistic synthetic dataset - xR-EgoPose - offering 383K frames of high quality renderings ofpeople with a diversity of skin tones, body shapes, clothing, in a variety of backgrounds and lighting conditions, performing a range of actions. Our experiments show that the high variability in our new synthetic training corpus leads to good generalization to real world footage and to state of the art results on real world datasets with ground truth. Moreover, an evaluation on the Human3.6M benchmark shows that the performance of our method is on par with top performing approaches on the more classic problem of 3D human pose from a third person viewpoint

CAD techniques for microwave circuits

In little more than 10 years computer-aided design (CAD) of microwave circuits has moved from dumb terminals on mainframe computers to PCs, and now to powerful RISC workstations. Commercial CAD software now integrates the various stages of microwave circuit design: schematic capture, simulation and layout. This paper reviews the different CAD packages that are available for microwave circuit design. The basic principles employed in the modelling of microstrip circuits are introduced and the reasons for the extensive use of frequency-domain simulations are explored. The developments in nonlinear, electromagnetic and system-level simulation methods are described.The authors would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council, and the Comisidn Interministerial de Ciencia y Technologia (CICr?‘), Spain, under the project TIC95-0983-C03-02. We would like to thank Hewlett Packard, Barnard Microsystems, Sonnet Software, Optimization Systems Associates, Kimberley Communications Consultants and Ansoft Corporation for their generous educational discounting. The assistance of Dr. D. M. Brookbanks at GEC-Marconi Materials Technology Ltd. (Caswell) is gratefully acknowledged

Harmonic suppression in microstrip dual-mode ring-resonator bandpass filters

This paper introduces two new topologies for rejecting the harmonics in microstrip ring resonator filters. First one uses 50 Ω spur line filter structures placed at the input and output of the ring to suppress the first harmonic. Second topology incorporates low-pass structures into the ring for elimination of the harmonic

Aviram-Ratner rectifying mechanism for DNA base pair sequencing through graphene nanogaps

We demonstrate that biological molecules such as Watson-Crick DNA base pairs can behave as biological Aviram-Ratner electrical rectifiers because of the spatial separation and weak hydrogen bonding between the nucleobases. We have performed a parallel computational implementation of the ab-initio non-equilibrium Green's function (NEGF) theory to determine the electrical response of graphene---base-pair---graphene junctions. The results show an asymmetric (rectifying) current-voltage response for the Cytosine-Guanine base pair adsorbed on a graphene nanogap. In sharp contrast we find a symmetric response for the Thymine-Adenine case. We propose applying the asymmetry of the current-voltage response as a sensing criterion to the technological challenge of rapid DNA sequencing via graphene nanogaps

Structured uncertainty prediction networks

This paper is the first work to propose a network to predict a structured uncertainty distribution for a synthesized image. Previous approaches have been mostly limited to predicting diagonal covariance matrices. Our novel model learns to predict a full Gaussian covariance matrix for each reconstruction, which permits efficient sampling and likelihood evaluation. We demonstrate that our model can accurately reconstruct ground truth correlated residual distributions for synthetic datasets and generate plausible high frequency samples for real face images. We also illustrate the use of these predicted covariances for structure preserving image denoising

Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image

We propose a unified formulation for the problem of 3D human pose estimation from a single raw RGB image that reasons jointly about 2D joint estimation and 3D pose reconstruction to improve both tasks. We take an integrated approach that fuses probabilistic knowledge of 3D human pose with a multi-stage CNN architecture and uses the knowledge of plausible 3D landmark locations to refine the search for better 2D locations. The entire process is trained end-to-end, is extremely efficient and obtains state-of-the-art results on Human3.6M outperforming previous approaches both on 2D and 3D errors

A proposal to improve the authentication process in m-health environments

Special Section: Mission Critical Public-Safety Communications: Architectures, Enabling Technologies, and Future Applications One of the challenges of mobile health is to provide a way of maintaining privacy in the access to the data. Especially, when using ICT for providing access to health services and information. In these scenarios, it is essential to determine and verify the identity of users to ensure the security of the network. A way of authenticating the identity of each patient, doctor or any stakeholder involved in the process is to use a software application that analyzes the face of them through the cams integrated in their devices. The selection of an appropriate facial authentication software application requires a fair comparison between alternatives through a common database of face images. Users usually carry out authentication with variations in their aspects while accessing to health services. This paper presents both 1) a database of facial images that combines the most common variations that can happen in the participants and 2) an algorithm that establishes different levels of access to the data based on data sensitivity levels and the accuracy of the authentication