20,493 research outputs found

    Testing the nature of dark compact objects: a status report

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    Very compact objects probe extreme gravitational fields and may be the key to understand outstanding puzzles in fundamental physics. These include the nature of dark matter, the fate of spacetime singularities, or the loss of unitarity in Hawking evaporation. The standard astrophysical description of collapsing objects tells us that massive, dark and compact objects are black holes. Any observation suggesting otherwise would be an indication of beyond-the-standard-model physics. Null results strengthen and quantify the Kerr black hole paradigm. The advent of gravitational-wave astronomy and precise measurements with very long baseline interferometry allow one to finally probe into such foundational issues. We overview the physics of exotic dark compact objects and their observational status, including the observational evidence for black holes with current and future experiments.Comment: 76 pages + references. Invited review article for Living Reviews in Relativity. v3: Overall improvements and references added, a few typos corrected. Version to appear in LR

    AirCode: Unobtrusive Physical Tags for Digital Fabrication

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    We present AirCode, a technique that allows the user to tag physically fabricated objects with given information. An AirCode tag consists of a group of carefully designed air pockets placed beneath the object surface. These air pockets are easily produced during the fabrication process of the object, without any additional material or postprocessing. Meanwhile, the air pockets affect only the scattering light transport under the surface, and thus are hard to notice to our naked eyes. But, by using a computational imaging method, the tags become detectable. We present a tool that automates the design of air pockets for the user to encode information. AirCode system also allows the user to retrieve the information from captured images via a robust decoding algorithm. We demonstrate our tagging technique with applications for metadata embedding, robotic grasping, as well as conveying object affordances.Comment: ACM UIST 2017 Technical Paper

    Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts

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    This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies

    Key characteristics of specular stereo.

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    Because specular reflection is view-dependent, shiny surfaces behave radically differently from matte, textured surfaces when viewed with two eyes. As a result, specular reflections pose substantial problems for binocular stereopsis. Here we use a combination of computer graphics and geometrical analysis to characterize the key respects in which specular stereo differs from standard stereo, to identify how and why the human visual system fails to reconstruct depths correctly from specular reflections. We describe rendering of stereoscopic images of specular surfaces in which the disparity information can be varied parametrically and independently of monocular appearance. Using the generated surfaces and images, we explain how stereo correspondence can be established with known and unknown surface geometry. We show that even with known geometry, stereo matching for specular surfaces is nontrivial because points in one eye may have zero, one, or multiple matches in the other eye. Matching features typically yield skew (nonintersecting) rays, leading to substantial ortho-epipolar components to the disparities, which makes deriving depth values from matches nontrivial. We suggest that the human visual system may base its depth estimates solely on the epipolar components of disparities while treating the ortho-epipolar components as a measure of the underlying reliability of the disparity signals. Reconstructing virtual surfaces according to these principles reveals that they are piece-wise smooth with very large discontinuities close to inflection points on the physical surface. Together, these distinctive characteristics lead to cues that the visual system could use to diagnose specular reflections from binocular information.The work was funded by the Wellcome Trust (grants 08459/Z/07/Z & 095183/Z/10/Z) and the EU Marie Curie Initial Training Network “PRISM” (FP7-PEOPLE-2012-ITN, Agreement: 316746).This is the author accepted manuscript. The final version is available from ARVO via http://dx.doi.org/10.1167/14.14.1

    Development of ultrasound to measure deformation of functional spinal units in cervical spine

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    Neck pain is a pervasive problem in the general population, especially in those working in vibrating environments, e.g. military troops and truck drivers. Previous studies showed neck pain was strongly associated with the degeneration of intervertebral disc, which is commonly caused by repetitive loading in the work place. Currently, there is no existing method to measure the in-vivo displacement and loading condition of cervical spine on the site. Therefore, there is little knowledge about the alternation of cervical spine functionality and biomechanics in dynamic environments. In this thesis, a portable ultrasound system was explored as a tool to measure the vertebral motion and functional spinal unit deformation. It is hypothesized that the time sequences of ultrasound imaging signals can be used to characterize the deformation of cervical spine functional spinal units in response to applied displacements and loading. Specifically, a multi-frame tracking algorithm is developed to measure the dynamic movement of vertebrae, which is validated in ex-vivo models. The planar kinematics of the functional spinal units is derived from a dual ultrasound system, which applies two ultrasound systems to image C-spine anteriorly and posteriorly. The kinematics is reconstructed from the results of the multi-frame movement tracking algorithm and a method to co-register ultrasound vertebrae images to MRI scan. Using the dual ultrasound, it is shown that the dynamic deformation of functional spinal unit is affected by the biomechanics properties of intervertebral disc ex-vivo and different applied loading in activities in-vivo. It is concluded that ultrasound is capable of measuring functional spinal units motion, which allows rapid in-vivo evaluation of C-spine in dynamic environments where X-Ray, CT or MRI cannot be used.2020-02-20T00:00:00

    On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks

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    Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks. These are typically not compared nor discussed in the literature due to a lack of multi-modal datasets. Texture-less regions are problematic for structure from motion and stereo, reflective material poses issues for active sensing, and distances for translucent objects are intricate to measure with existing hardware. Training on inaccurate or corrupt data induces model bias and hampers generalisation capabilities. These effects remain unnoticed if the sensor measurement is considered as ground truth during the evaluation. This paper investigates the effect of sensor errors for the dense 3D vision tasks of depth estimation and reconstruction. We rigorously show the significant impact of sensor characteristics on the learned predictions and notice generalisation issues arising from various technologies in everyday household environments. For evaluation, we introduce a carefully designed dataset\footnote{dataset available at https://github.com/Junggy/HAMMER-dataset} comprising measurements from commodity sensors, namely D-ToF, I-ToF, passive/active stereo, and monocular RGB+P. Our study quantifies the considerable sensor noise impact and paves the way to improved dense vision estimates and targeted data fusion.Comment: Accepted at CVPR 2023, Main Paper + Supp. Mat. arXiv admin note: substantial text overlap with arXiv:2205.0456

    Cavitation Induction by Projectile Impacting on a Water Jet

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    The present paper focuses on the simulation of the high-velocity impact of a projectile impacting on a water-jet, causing the onset, development and collapse of cavitation. The simulation of the fluid motion is carried out using an explicit, compressible, density-based solver developed by the authors using the OpenFOAM library. It employs a barotropic two-phase flow model that simulates the phase-change due to cavitation and considers the co-existence of non-condensable and immiscible air. The projectile is considered to be rigid while its motion through the computational domain is modelled through a direct-forcing Immersed Boundary Method. Model validation is performed against the experiments of Field et al. [Field, J., Camus, J. J., Tinguely, M., Obreschkow, D., Farhat, M., 2012. Cavitation in impacted drops and jets and the effect on erosion damage thresholds. Wear 290–291, 154–160. doi:10.1016/j.wear.2012.03.006. URL http://www.sciencedirect.com/science/article/pii/S0043164812000968 ], who visualised cavity formation and shock propagation in liquid impacts at high velocities. Simulations unveil the shock structures and capture the high-speed jetting forming at the impact location, in addition to the subsequent cavitation induction and vapour formation due to refraction waves. Moreover, model predictions provide quantitative information and a better insight on the flow physics that has not been identified from the reported experimental data, such as shock-wave propagation, vapour formation quantity and induced pressures. Furthermore, evidence of the Richtmyer-Meshkov instability developing on the liquid-air interface are predicted when sufficient dense grid resolution is utilised

    Computational Multimedia for Video Self Modeling

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    Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of oneself. This is the idea behind the psychological theory of self-efficacy - you can learn or model to perform certain tasks because you see yourself doing it, which provides the most ideal form of behavior modeling. The effectiveness of VSM has been demonstrated for many different types of disabilities and behavioral problems ranging from stuttering, inappropriate social behaviors, autism, selective mutism to sports training. However, there is an inherent difficulty associated with the production of VSM material. Prolonged and persistent video recording is required to capture the rare, if not existed at all, snippets that can be used to string together in forming novel video sequences of the target skill. To solve this problem, in this dissertation, we use computational multimedia techniques to facilitate the creation of synthetic visual content for self-modeling that can be used by a learner and his/her therapist with a minimum amount of training data. There are three major technical contributions in my research. First, I developed an Adaptive Video Re-sampling algorithm to synthesize realistic lip-synchronized video with minimal motion jitter. Second, to denoise and complete the depth map captured by structure-light sensing systems, I introduced a layer based probabilistic model to account for various types of uncertainties in the depth measurement. Third, I developed a simple and robust bundle-adjustment based framework for calibrating a network of multiple wide baseline RGB and depth cameras
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