Augmenting depth camera output using photometric stereo

We present a system for augmenting depth camera output using multispectral photometric stereo. The technique is demonstrated using a Kinect sensor and is able to produce geometry independently for each frame. Improved reconstruction is demonstrated using the Kinect's inbuilt RGB camera and further improvements are achieved by introducing an additional high resolution camera. As well as qualitative improvements in reconstruction a quantitative reduction in temporal noise is shown. As part of the system an approach is presented for relaxing the assumption of multispectral photometric stereo that scenes are of constant chromaticity to the assumption that scenes contain multiple piecewise constant chromaticities.

Single camera pose estimation using Bayesian filtering and Kinect motion priors

Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not ideal and somewhat inelegant as it results in large processing burdens, and instead attempt to incorporate these constraints through priors obtained directly from training data. A prior distribution covering the probability of a human pose occurring is used to incorporate likely human poses. This distribution is obtained offline, by fitting a Gaussian mixture model to a large dataset of recorded human body poses, tracked using a Kinect sensor. We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework. Our model can be viewed as a mixture of discrete Ornstein-Uhlenbeck processes, in that states behave as random walks, but drift towards a set of typically observed poses. This model is combined with measurements of the human head and hand positions, using recursive Bayesian estimation to incorporate temporal information. Measurements are obtained using face detection and a simple skin colour hand detector, trained using the detected face. The suggested model is designed with analytical tractability in mind and we show that the pose tracking can be Rao-Blackwellised using the mixture Kalman filter, allowing for computational efficiency while still incorporating bio-mechanical properties of the upper body. In addition, the use of the proposed upper body model allows reliable three-dimensional pose estimates to be obtained indirectly for a number of joints that are often difficult to detect using traditional object recognition strategies. Comparisons with Kinect sensor results and the state of the art in 2D pose estimation highlight the efficacy of the proposed approach.

Low power consumption and high sensitivity carbon monoxide gas sensor using indium oxide nanowire.

In this paper, micro gas sensor was fabricated using indium oxide nanowire for effective gas detection and monitoring system. Indium oxide nanowire was grown using thermal CVD, and their structural properties were examined by the SEM, XRD and TEM. The electric properties for microdropped indium oxide nanowire device were measured, and gas response characteristics were examined for CO gas. Sensors showed high sensitivity and stability for CO gas. And with below 20 mw power consumption, 5 ppm CO could be detected.

A novel, sensitive potentiometric hydrocarbon sensor for high-vacuum applications.

A potentiometric device based on interfacing a solid electrolyte oxygen ion conductor with a thin platinum film acts as a robust, reproducible sensor for the detection of hydrocarbons in high- or ultrahigh-vacuum environments. Sensitivities in the order of approximately 5 x 10(-10) mbar are achievable under open circuit conditions, with good selectivity for discrimination between n-butane on one hand and toluene, n-octane, n-hexane, and 1-butene on the other hand. The sensor's sensitivity may be tuned by operating under constant current (closed circuit) conditions; injection of anodic current is also a very effective means of restoring a clean sensing surface at any desired point. XPS data and potentiometric measurements confirm the proposed mode of sensing action: the steady-state coverage of Oa, which sets the potential of the Pt sensing electrode, is determined by the partial pressure and dissociative sticking probability of the impinging hydrocarbon. The principles established here provide the basis for a viable, inherently flexible, and promising means for the sensitive and selective detection of hydrocarbons under demanding conditions.

Frequency diversity measurements at 2.4 GHz for wireless sensor networks deployed in tunnels

Wireless Sensor Networks (WSNs) which utilise IEEE 802.15.4 technology operate primarily in the 2.4 GHz globally compatible ISM band. However, the wireless propagation channel in this crowded band is notoriously variable and unpredictable, and it has a significant impact on the coverage range and quality of the radio links between the wireless nodes. Therefore, the use of Frequency Diversity (FD) has potential to ameliorate this situation. In this paper, the possible benefits of using FD in a tunnel environment have been quantified by performing accurate propagation measurements using modified and calibrated off-the-shelf 802.15.4 based sensor motes in the disused Aldwych underground railway tunnel. The objective of this investigation is to characterise the performance of FD in this confined environment. Cross correlation coefficients are calculated from samples of the received power on a number of frequency channels gathered during the field measurements. The low measured values of the cross correlation coefficients indicate that applying FD at 2.4 GHz will improve link performance in a WSN deployed in a tunnel. This finding closely matches results obtained by running a computational simulation of the tunnel radio propagation using a 2D Finite-Difference Time-Domain (FDTD) method. ©2009 IEEE.