15 research outputs found
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving
Key-point-based scene understanding is fundamental for autonomous driving
applications. At the same time, optical flow plays an important role in many
vision tasks. However, due to the implicit bias of equal attention on all
points, classic data-driven optical flow estimation methods yield less
satisfactory performance on key points, limiting their implementations in
key-point-critical safety-relevant scenarios. To address these issues, we
introduce a points-based modeling method that requires the model to learn
key-point-related priors explicitly. Based on the modeling method, we present
FocusFlow, a framework consisting of 1) a mix loss function combined with a
classic photometric loss function and our proposed Conditional Point Control
Loss (CPCL) function for diverse point-wise supervision; 2) a conditioned
controlling model which substitutes the conventional feature encoder by our
proposed Condition Control Encoder (CCE). CCE incorporates a Frame Feature
Encoder (FFE) that extracts features from frames, a Condition Feature Encoder
(CFE) that learns to control the feature extraction behavior of FFE from input
masks containing information of key points, and fusion modules that transfer
the controlling information between FFE and CFE. Our FocusFlow framework shows
outstanding performance with up to +44.5% precision improvement on various key
points such as ORB, SIFT, and even learning-based SiLK, along with exceptional
scalability for most existing data-driven optical flow methods like PWC-Net,
RAFT, and FlowFormer. Notably, FocusFlow yields competitive or superior
performances rivaling the original models on the whole frame. The source code
will be available at https://github.com/ZhonghuaYi/FocusFlow_official.Comment: The source code of FocusFlow will be available at
https://github.com/ZhonghuaYi/FocusFlow_officia
SVFormer: Semi-supervised Video Transformer for Action Recognition
Semi-supervised action recognition is a challenging but critical task due to
the high cost of video annotations. Existing approaches mainly use
convolutional neural networks, yet current revolutionary vision transformer
models have been less explored. In this paper, we investigate the use of
transformer models under the SSL setting for action recognition. To this end,
we introduce SVFormer, which adopts a steady pseudo-labeling framework (ie,
EMA-Teacher) to cope with unlabeled video samples. While a wide range of data
augmentations have been shown effective for semi-supervised image
classification, they generally produce limited results for video recognition.
We therefore introduce a novel augmentation strategy, Tube TokenMix, tailored
for video data where video clips are mixed via a mask with consistent masked
tokens over the temporal axis. In addition, we propose a temporal warping
augmentation to cover the complex temporal variation in videos, which stretches
selected frames to various temporal durations in the clip. Extensive
experiments on three datasets Kinetics-400, UCF-101, and HMDB-51 verify the
advantage of SVFormer. In particular, SVFormer outperforms the state-of-the-art
by 31.5% with fewer training epochs under the 1% labeling rate of Kinetics-400.
Our method can hopefully serve as a strong benchmark and encourage future
search on semi-supervised action recognition with Transformer networks
Towards Neutron Transformation Searches
To probe the origins of the baryon asymmetry, baryon number violation, the last unconfirmed Sakharov condition, must be definitively observed experimentally. Similarly, the nature of dark matter is currently unknown, and calls out for new candidates to be investigated. Each of these issues can be considered through the study of neutron transformations.
Some rare baryon number violating processes, such as neutron-antineutron transformations, are expected to probe baryogenesis. Here, I show progress on this discovery target through construction of more accurate Monte Carlo models, the design of future detectors, creation of more complete atmospheric neutrino background simulations, and use of automated analysis techniques within the the NNBAR/HIBEAM experimental program at the European Spallation Source (ESS) and the Deep Underground Neutrino Experiment (DUNE). First simulation-based sensitivities for these experiments will be discussed. Modeling of rare neutron-antineutron transformation and subsequent annihilation will be discussed at length for multiple nuclei useful to these and other collaborations. To go along with this work, more comprehensive lepton-scattering nuclear models must be integrated into neutrino event generators for proper atmospheric neutrino background simulations. I discuss the first furnishing of these backgrounds for DUNE, and I highlight a potential path forward for the community in this vein using precision electron scattering modeling as a facsimile.
Aspects of other potentially related neutron--mirror-neutron oscillations pertinent to dark matter and the neutron lifetime anomaly will also be considered for the ESS HIBEAM experiment. Here, I will present the first experimental sensitivity calculations for a broad range of modular experimental setups which will serve as research and design stepping stones toward NNBAR while producing a multitude of physics results over short time scales
High Resolution Imaging and the Formation of Stars and Planets
Understanding the formation of stellar and planetary systems is one of the great challenges of contemporary astrophysics. This thesis describes progress towards understanding these processes, through advancement of techniques to enable high resolution imaging of faint companions and other structures in the immediate environs of young stars. To ensure optimal performance in an era of large segmented telescopes, techniques to precisely cophase the mirror segments are required. In this thesis we propose the Fizeau Interferometric Cophasing of Segmented Mirrors algorithm, and present the results of testing both numerically and through experiment. We help to rectify a lack of observational evidence with which to test brown dwarf evolutionary models, by laying the foundation for an orbital monitoring survey of 19 brown dwarf binary systems and reporting the discovery of an additional 7 low mass companions to intermediate mass stars. We perform a Non-Redundant Masking (NRM) survey targeting the 1\,Myr old Ophiuchus star forming region. Both binary statistics and the relationship between multiplicity and the presence of a circumstellar disk are explored, providing many results similar to those from older regions. This helps frame the time evolution of effects related to dynamical interactions in binary systems, and the timescale of disk dissipation, with profound implications for giant planet formation. In thesis we also present the results of commissioning for the Gemini Planet Imager Non-Redundant Masking mode. These results indicate that the addition of an Extreme Adaptive Optics systems has substantially improved the performance of NRM compared to previous instruments. Finally, the transition disk T Cha is studied with multi-epoch NRM data, showing that the signal previously interpreted as a planetary companion is more likely to be the result of forward scattering from the inclined outer disk
High Resolution Imaging and the Formation of Stars and Planets
Understanding the formation of stellar and planetary systems is one of the great challenges of contemporary astrophysics. This thesis describes progress towards understanding these processes, through advancement of techniques to enable high resolution imaging of faint companions and other structures in the immediate environs of young stars. To ensure optimal performance in an era of large segmented telescopes, techniques to precisely cophase the mirror segments are required. In this thesis we propose the Fizeau Interferometric Cophasing of Segmented Mirrors algorithm, and present the results of testing both numerically and through experiment. We help to rectify a lack of observational evidence with which to test brown dwarf evolutionary models, by laying the foundation for an orbital monitoring survey of 19 brown dwarf binary systems and reporting the discovery of an additional 7 low mass companions to intermediate mass stars. We perform a Non-Redundant Masking (NRM) survey targeting the 1\,Myr old Ophiuchus star forming region. Both binary statistics and the relationship between multiplicity and the presence of a circumstellar disk are explored, providing many results similar to those from older regions. This helps frame the time evolution of effects related to dynamical interactions in binary systems, and the timescale of disk dissipation, with profound implications for giant planet formation. In thesis we also present the results of commissioning for the Gemini Planet Imager Non-Redundant Masking mode. These results indicate that the addition of an Extreme Adaptive Optics systems has substantially improved the performance of NRM compared to previous instruments. Finally, the transition disk T Cha is studied with multi-epoch NRM data, showing that the signal previously interpreted as a planetary companion is more likely to be the result of forward scattering from the inclined outer disk
Searches for new physics using low energy electron recoils in the LUX and LZ experiments
There is evidence, on a range of astrophysical and cosmological scales, that most of the matter in the universe is comprised of invisible dark matter. The particle nature of this dark matter is inconsistent with the Standard Model (SM) of particle physics and, along with other unexplained phenomena, implies the existence of new physics beyond the SM. A range of dark matter models and SM extensions exist, predicting a broad range of new phenomena. One popular dark matter candidate is Weakly Interacting Massive Particles (WIMPs), but after several decades of experimental efforts there has been no conclusive detection. As a result, there is increased interest in alternative models, such as axions or hidden sector dark matter, motivating broader search strategies.
Direct detection experiments typically aim to detect WIMPs scattering off nuclei in a terrestrial detector. However, they can also be used to search for electron recoil signals resulting from other new physics models. The LUX experiment, and its successor LUX-ZEPLIN (LZ), use xenon dual phase time projection chamber technology to search for dark matter.
In this work the mirror dark matter (MDM) model will be examined, with the world’s first direct detection search for MDM, using LUX data. The result, published in Physical Review D [1], rules out much of the allowed parameter space for this model. LZ will have a larger exposure and lower backgrounds than LUX, giving improved sensitivity to rare events. A general approach for low energy electron recoil analyses in LZ has been used to find projected confidence limits for seven signal models, preprint [2]. The solar axion and MDM analyses will be described in detail here. If a new physics signal is detected it is important to characterise the model, often involving multiple model parameters. In this work a Bayesian approach is investigated for analysis with multiple parameters of interest, using a solar axion analysis as a test case
Complex flow physics & active plasma flow control in convoluted ducts
Convoluted, s-shaped ducts form an integral part of many subsystems in engineering applications and specifically the aviation industry. They are used, for example, as inlet ducts for fuselage embedded jet engines and as connector pipes between high and low pressure turbine or compressor stages. With a strong curvature and a diffusive nature, the geometry acts on the through-flow making it prone to separate and experience significant cross-stream pressure gradients. The geometry and resulting flow phenomena lead to a non-uniform and highly unsteady flow field in the duct aft the inflection point. Those effects are detrimental to the overall performance of the convoluted duct, reducing the pressure recovery and increasing the distortion parameters.
S-shaped ducts have been studied by a large number of researchers for many years. Traditionally, many studies rely on steady state simulations and time averaged experimental data to characterise the flow in convoluted ducts and analyse their performance. However, more recent findings point to the need of transient data to fully understand the dynamic nature of the through-flow and discuss the complex flow physics. This is something that is lacking from many studies reported in the current literature.
This is addressed with computational fluid dynamics (CFD) studies of the through-flow in the s-duct using the open source tool OpenFOAM. First low fidelity, steady state simulations are set up before higher fidelity, transient delayed detached eddy simulations (DDES) are conducted. Baseline s-duct through-flow computations are validated against experimental data from literature with very good agreement of pressure recovery values, wall static pressure contours, and flow structures. CFD data is next post processed with statistical and modal decomposition methods. Coherent structures and phase information are obtained from the proper orthogonal decomposition (POD) and the dynamic mode decomposition (DMD) methods.
Modal decomposition analysis of DDES data confirms the existance of the horizontal shifing mode. Contrary to previous findings, the presence of a second vertical shifting mode is observed from DDES data. Occurance rates and phase information are determined from the DMD analysis.
The recent surge of interest in plasma actuators is clearly illustrated by the high research output that has been reported in literature. Dielectric barrier discharge (DBD) plasma actuators have been studied and successfully applied to control external aerodynamics on aerofoils and bluff bodies. However, successful flow control in convoluted ducts has not been reported with this technology for realistic Reynolds numbers.
The DBD plasma characterisation is conducted on two types of actuators: alternating current (ac) and nanosecond (ns) DBD plasma actuators. The Schlieren imaging technique is used with ns-DBD plasmas to record
density changes and establish the shock front strength and propagation speed with changing ambient pressure. Higher ambient pressures result in stronger shock waves; this has been observed irrespective of the actuator thickness. This might be explained with fewer air molecules to ionize at lower ambient pressures and hence a lower temperature from the exothermal recombination reactions.
For ac-DBD actuators, thinner dielectric materials outperformed thicker ones in terms of ionisation strength with constant voltage input. The smallest dielectric constant of the materials tested resulted in higher induced velocities. Using particle image velocimetry (PIV), a high gradient of velocity reduction with streamwise distance was recorded in the plasma jet. This is significant, as it shows plasma actuators have
mostly localised effects.
Experimental campaigns are set up such that the DBD experiments are coherent studies in their own right. However, the main purpose of plasma experiments in the context of this thesis is to collect data to validate
numerical plasma models. Those phenomenological plasma models are subsequently used for numerical flow control studies on the s-shaped duct. Phenomenological plasma models match the experimental data well when
tuned. However, the flow control studies did not show a performance improvement in the convoluted duct