POL-LWIR Vehicle Detection: Convolutional Neural Networks Meet Polarised Infrared Sensors

For vehicle autonomy, driver assistance and situational awareness, it is necessary to operate at day and night, and in all weather conditions. In particular, long wave infrared (LWIR) sensors that receive predominantly emitted radiation have the capability to operate at night as well as during the day. In this work, we employ a polarised LWIR (POL-LWIR) camera to acquire data from a mobile vehicle, to compare and contrast four different convolutional neural network (CNN) configurations to detect other vehicles in video sequences. We evaluate two distinct and promising approaches, two-stage detection (Faster-RCNN) and one-stage detection (SSD), in four different configurations. We also employ two different image decompositions: the first based on the polarisation ellipse and the second on the Stokes parameters themselves. To evaluate our approach, the experimental trials were quantified by mean average precision (mAP) and processing time, showing a clear trade-off between the two factors. For example, the best mAP result of 80.94% was achieved using Faster-RCNN, but at a frame rate of 6.4 fps. In contrast, MobileNet SSD achieved only 64.51% mAP, but at 53.4 fps.Comment: Computer Vision and Pattern Recognition Workshop 201

Linear Differential Constraints for Photo-polarimetric Height Estimation

In this paper we present a differential approach to photo-polarimetric shape estimation. We propose several alternative differential constraints based on polarisation and photometric shading information and show how to express them in a unified partial differential system. Our method uses the image ratios technique to combine shading and polarisation information in order to directly reconstruct surface height, without first computing surface normal vectors. Moreover, we are able to remove the non-linearities so that the problem reduces to solving a linear differential problem. We also introduce a new method for estimating a polarisation image from multichannel data and, finally, we show it is possible to estimate the illumination directions in a two source setup, extending the method into an uncalibrated scenario. From a numerical point of view, we use a least-squares formulation of the discrete version of the problem. To the best of our knowledge, this is the first work to consider a unified differential approach to solve photo-polarimetric shape estimation directly for height. Numerical results on synthetic and real-world data confirm the effectiveness of our proposed method.Comment: To appear at International Conference on Computer Vision (ICCV), Venice, Italy, October 22-29, 201

Polarisation measurements with a CdTe pixel array detector for Laue hard X-ray focusing telescopes

Polarimetry is an area of high energy astrophysics which is still relatively unexplored, even though it is recognized that this type of measurement could drastically increase our knowledge of the physics and geometry of high energy sources. For this reason, in the context of the design of a Gamma-Ray Imager based on new hard-X and soft gamma ray focusing optics for the next ESA Cosmic Vision call for proposals (Cosmic Vision 2015-2025), it is important that this capability should be implemented in the principal on-board instrumentation. For the particular case of wide band-pass Laue optics we propose a focal plane based on a thick pixelated CdTe detector operating with high efficiency between 60-600 keV. The high segmentation of this type of detector (1-2 mm pixel size) and the good energy resolution (a few keV FWHM at 500 keV) will allow high sensitivity polarisation measurements (a few % for a 10 mCrab source in 106s) to be performed. We have evaluated the modulation Q factors and minimum detectable polarisation through the use of Monte Carlo simulations (based on the GEANT 4 toolkit) for on and off-axis sources with power law emission spectra using the point spread function of a Laue lens in a feasible configuration.Comment: 10 pages, 6 pages. Accepted for publication in Experimental Astronom

Cryosphere Applications

Synthetic aperture radar (SAR) provides large coverage and high resolution, and it has been proven to be sensitive to both surface and near-surface features related to accumulation, ablation, and metamorphism of snow and firn. Exploiting this sensitivity, SAR polarimetry and polarimetric interferometry found application to land ice for instance for the estimation of wave extinction (which relates to sub surface ice volume structure) and for the estimation of snow water equivalent (which relates to snow density and depth). After presenting these applications, the Chapter proceeds by reviewing applications of SAR polarimetry to sea ice for the classification of different ice types, the estimation of thickness, and the characterisation of its surface. Finally, an application to the characterisation of permafrost regions is considered. For each application, the used (model-based) decomposition and polarimetric parameters are critically described, and real data results from relevant airborne campaigns and space borne acquisitions are reported

PoGOLite - A High Sensitivity Balloon-Borne Soft Gamma-ray Polarimeter

We describe a new balloon-borne instrument (PoGOLite) capable of detecting 10% polarisation from 200mCrab point-like sources between 25 and 80keV in one 6 hour flight. Polarisation measurements in the soft gamma-ray band are expected to provide a powerful probe into high-energy emission mechanisms as well as the distribution of magnetic fields, radiation fields and interstellar matter. At present, only exploratory polarisation measurements have been carried out in the soft gamma-ray band. Reduction of the large background produced by cosmic-ray particles has been the biggest challenge. PoGOLite uses Compton scattering and photo-absorption in an array of 217 well-type phoswich detector cells made of plastic and BGO scintillators surrounded by a BGO anticoincidence shield and a thick polyethylene neutron shield. The narrow FOV (1.25msr) obtained with well-type phoswich detector technology and the use of thick background shields enhance the detected S/N ratio. Event selections based on recorded phototube waveforms and Compton kinematics reduce the background to that expected for a 40-100mCrab source between 25 and 50keV. A 6 hour observation on the Crab will differentiate between the Polar Cap/Slot Gap, Outer Gap, and Caustic models with greater than 5 sigma; and also cleanly identify the Compton reflection component in the Cygnus X-1 hard state. The first flight is planned for 2010 and long-duration flights from Sweden to Northern Canada are foreseen thereafter.Comment: 11 pages, 11 figures, 2 table

Investigation of Microstructural and Carbon Deposition Effects in SOFC Anodes Through Modelling and Experiments

The investigation of the SOFC anode microstructural properties affected by microstructural parameters and degradation is the focus of this research. Imaging and image processing techniques are developed to achieve quantification of the anode microstructural information. The analytical and Computational Fluid Dynamics based modelling of the microstructure including the degradation effects developed in this work will enable the microstructure optimisation for achieving performance enhancements

Analysis of infrared polarisation signatures for vehicle detection

Thermal radiation emitted from objects within a scene tends to be partially polarised in a direction parallel to the surface normal, to an extent governed by properties of the surface material. This thesis investigates whether vehicle detection algorithms can be improved by the additional measurement of polarisation state as well as intensity in the long wave infrared. Knowledge about the polarimetric properties of scenes guides the development of histogram based and cluster based descriptors which are used in a traditional classification framework. The best performing histogram based method, the Polarimetric Histogram, which forms a descriptor based on the polarimetric vehicle signature is shown to outperform the standard Histogram of Oriented Gradients descriptor which uses intensity imagery alone. These descriptors then lead to a novel clustering algorithm which, at a false positive rate of 10−2 is shown to improve upon the Polarimetric Histogram descriptor, increasing the true positive rate from 0.19 to 0.63. In addition, a multi-modal detection framework which combines thermal intensity hotspot and polarimetric hotspot detections with a local motion detector is presented. Through the combination of these detectors, the false positive rate is shown to be reduced when compared to the result of individual detectors in isolation

On Recognizing Transparent Objects in Domestic Environments Using Fusion of Multiple Sensor Modalities

Current object recognition methods fail on object sets that include both diffuse, reflective and transparent materials, although they are very common in domestic scenarios. We show that a combination of cues from multiple sensor modalities, including specular reflectance and unavailable depth information, allows us to capture a larger subset of household objects by extending a state of the art object recognition method. This leads to a significant increase in robustness of recognition over a larger set of commonly used objects.Comment: 12 page