Dense 3D Reconstruction in Dynamic Environments

3D reconstruction/dense mapping can be used in many applications such as medical imaging, virtual reality, navigations, etc. In this dissertation, we discussed the different state-of-the-art approaches for 3D reconstruction using visual sensors. Current dense space reconstruction representation can be point cloud, octomap, voxel, surfel, etc. The system generally requires the scan of the environment along with the tracking estimation of the moving sensors. This dissertation provides solutions to the dense 3D reconstruction with visual/visual-inertial sensors in a dynamic environment and tests it both on the CPU and GPU. We decouple the sensor tracking and dense reconstruction. Additionally, we develop a learning-based segmentation technique to detect possible dynamic objects and use the static objects for robust sensor tracking. Then we apply the tracking result to the reconstruction system. We modulize our system so each part (tracking, segmentation, reconstruction) can be replaced in the future by a more advanced tracking/mapping system for better performance. The source code is shared for the benefit of the community1 .</p

Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization

Kalman filters are routinely used for many data fusion applications including navigation, tracking, and simultaneous localization and mapping problems. However, significant time and effort is frequently required to tune various Kalman filter model parameters, e.g. process noise covariance, pre-whitening filter models for non-white noise, etc. Conventional optimization techniques for tuning can get stuck in poor local minima and can be expensive to implement with real sensor data. To address these issues, a new "black box" Bayesian optimization strategy is developed for automatically tuning Kalman filters. In this approach, performance is characterized by one of two stochastic objective functions: normalized estimation error squared (NEES) when ground truth state models are available, or the normalized innovation error squared (NIS) when only sensor data is available. By intelligently sampling the parameter space to both learn and exploit a nonparametric Gaussian process surrogate function for the NEES/NIS costs, Bayesian optimization can efficiently identify multiple local minima and provide uncertainty quantification on its results.Comment: Final version presented at FUSION 2018 Conference, Cambridge, UK, July 2018 (submitted June 1, 2018

Deletion of TRPC6 attenuates NMDA receptor-mediated Ca\u3csup\u3e2+\u3c/sup\u3e Entry and Ca\u3csup\u3e2+\u3c/sup\u3e-induced neurotoxicity following cerebral ischemia and oxygen-glucose deprivation

Transient receptor potential canonical 6 (TRPC6) channels are permeable to Na+ and Ca2+ and are widely expressed in the brain. In this study, the role of TRPC6 was investigated following ischemia/reperfusion (I/R) and oxygen-glucose deprivation (OGD). We found that TRPC6 expression was increased in wild-type (WT) mice cortical neurons following I/R and in primary neurons with OGD, and that deletion of TRPC6 reduced the I/R-induced brain infarct in mice and the OGD- /neurotoxin-induced neuronal death. Using live-cell imaging to examine intracellular Ca2+ levels ([Ca2+]i), we found that OGD induced a significant higher increase in glutamate-evoked Ca2+ influx compared to untreated control and such an increase was reduced by TRPC6 deletion. Enhancement of TRPC6 expression using AdCMV-TRPC6-GFP infection in WT neurons increased [Ca2+]i in response to glutamate application compared to AdCMV-GFP control. Inhibition of N-methyl-d-aspartic acid receptor (NMDAR) with MK801 decreased TRPC6-dependent increase of [Ca2+]i in TRPC6 infected cells, indicating that such a Ca2+ influx was NMDAR dependent. Furthermore, TRPC6-dependent Ca2+ influx was blunted by blockade of Na+ entry in TRPC6 infected cells. Finally, OGD-enhanced Ca2+ influx was reduced, but not completely blocked, in the presence of voltage-dependent Na+ channel blocker tetrodotoxin (TTX) and dl-α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) blocker CNQX. Altogether, we concluded that I/R-induced brain damage was, in part, due to upregulation of TRPC6 in cortical neurons. We postulate that overexpression of TRPC6 following I/R may induce neuronal death partially through TRPC6-dependent Na+ entry which activated NMDAR, thus leading to a damaging Ca2+ overload. These findings may provide a potential target for future intervention in stroke-induced brain damage

Deletion of TRPC6 attenuates NMDA receptor-mediated Ca\u3csup\u3e2+\u3c/sup\u3e Entry and Ca\u3csup\u3e2+\u3c/sup\u3e-induced neurotoxicity following cerebral ischemia and oxygen-glucose deprivation

Transient receptor potential canonical 6 (TRPC6) channels are permeable to Na+ and Ca2+ and are widely expressed in the brain. In this study, the role of TRPC6 was investigated following ischemia/reperfusion (I/R) and oxygen-glucose deprivation (OGD). We found that TRPC6 expression was increased in wild-type (WT) mice cortical neurons following I/R and in primary neurons with OGD, and that deletion of TRPC6 reduced the I/R-induced brain infarct in mice and the OGD- /neurotoxin-induced neuronal death. Using live-cell imaging to examine intracellular Ca2+ levels ([Ca2+]i), we found that OGD induced a significant higher increase in glutamate-evoked Ca2+ influx compared to untreated control and such an increase was reduced by TRPC6 deletion. Enhancement of TRPC6 expression using AdCMV-TRPC6-GFP infection in WT neurons increased [Ca2+]i in response to glutamate application compared to AdCMV-GFP control. Inhibition of N-methyl-d-aspartic acid receptor (NMDAR) with MK801 decreased TRPC6-dependent increase of [Ca2+]i in TRPC6 infected cells, indicating that such a Ca2+ influx was NMDAR dependent. Furthermore, TRPC6-dependent Ca2+ influx was blunted by blockade of Na+ entry in TRPC6 infected cells. Finally, OGD-enhanced Ca2+ influx was reduced, but not completely blocked, in the presence of voltage-dependent Na+ channel blocker tetrodotoxin (TTX) and dl-α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) blocker CNQX. Altogether, we concluded that I/R-induced brain damage was, in part, due to upregulation of TRPC6 in cortical neurons. We postulate that overexpression of TRPC6 following I/R may induce neuronal death partially through TRPC6-dependent Na+ entry which activated NMDAR, thus leading to a damaging Ca2+ overload. These findings may provide a potential target for future intervention in stroke-induced brain damage

Vector space-time wave packets

Space-time wave packets (STWPs) are propagation-invariant pulsed beams whose characteristics stem from the tight association between their spatial and temporal degrees of freedom. Until recently, only scalar STWPs have been synthesized in the form of light sheets. Here we synthesize vector STWPs that are localized in all dimensions by preparing polarization-structured spatiotemporal spectra and unveil the polarization distribution over the STWP volume via time-resolved complex field measurements. Such vector STWPs are endowed with cylindrically symmetric polarization vector structures, which require joint manipulation of the spatial, temporal, and polarization degrees of freedom of the optical field. These results may be useful in particle manipulation, and in nonlinear and quantum optics

Phase and Channel Estimation for High-Capacity Phase-Asynchronous Mode-Division Multiplexing Multiple-Input Multiple-Output Free-Space Optical Communications in Strong Turbulent Channels

In this paper, we propose a novel pilot-aided phase and channel estimation algorithm for coherent mode-division multiplexing multiple-input multiple-output free-space optical communication system. This algorithm enables the implementation of advanced multiple-input multiple-output decoders, leading to a significantly better bit error rate performance. This algorithm also supports phase-asynchronous light sources at each transmit and receive channel, significantly reducing the hardware requirements. Moreover, it has low computational complexity and Cramér-Rao lower bound approaching estimation performance. In our proof-of-concept experiment, we employed 10 decorrelated channels to achieve a record-high 689.2 Gbit/s/wavelength line rate in strong turbulence, verifying the feasibility of our phase and channel estimation algorithm

Structured light enhanced machine learning for fiber bend sensing

The intricate optical distortions that occur when light interacts with complex media, such as few- or multi-mode optical fiber, often appear random in origin and are a fundamental source of error for communication and sensing systems. We propose the use of orbital angular momentum (OAM) feature extraction to mitigate phase-noise and allow for the use of intermodal-coupling as an effective tool for fiber sensing. OAM feature extraction is achieved by passive all-optical OAM demultiplexing, and we demonstrate fiber bend tracking with 94.1% accuracy. Conversely, an accuracy of only 14% was achieved for determining the same bend positions when using a convolutional-neural-network trained with intensity measurements of the output of the fiber. Further, OAM feature extraction used 120 times less information for training compared to intensity image based measurements. This work indicates that structured light enhanced machine learning could be used in a wide range of future sensing technologies

Biodegradable PEG-poly(ω-pentadecalactone- co - p -dioxanone) nanoparticles for enhanced and sustained drug delivery to treat brain tumors

Intracranial delivery of therapeutic agents is limited by penetration beyond the blood-brain barrier (BBB) and rapid metabolism of the drugs that are delivered. Convection-enhanced delivery (CED) of drugloaded nanoparticles (NPs) provides for local administration, control of distribution, and sustained drug release. While some investigators have shown that repeated CED procedures are possible, longer periods of sustained release could eliminate the need for repeated infusions, which would enhance safety and translatability of the approach. Here, we demonstrate that nanoparticles formed from poly(ethylene glycol)-poly(u-pentadecalactone-co-p-dioxanone) block copolymers [PEG-poly(PDL-co- DO)] are highly efficient nanocarriers that provide long-term release: small nanoparticles (less than 100 nm in diameter) continuously released a radiosensitizer (VE822) over a period of several weeks in vitro, provided widespread intracranial drug distribution during CED, and yielded significant drug retention within the brain for over 1 week. One advantage of PEG-poly(PDL-co-DO) nanoparticles is that hydrophobicity can be tuned by adjusting the ratio of hydrophobic PDL to hydrophilic DO monomers, thus making it possible to achieve a wide range of drug release rates and drug distribution profiles. When administered by CED to rats with intracranial RG2 tumors, and combined with a 5-day course of fractionated radiation therapy, VE822-loaded PEG-poly(PDL-co-DO) NPs significantly prolonged survival when compared to free VE822. Thus, PEG-poly(PDL-co-DO) NPs represent a new type of versatile nanocarrier system with potential for sustained intracranial delivery of therapeutic agents to treat brain tumors

Degradation of light carrying orbital angular momentum by ballistic scattering

Structured light can enhance the functionality of optical communication and sensing systems. Dense scattering environments such as those experienced in coastal water and foggy conditions result in degradation of structured optical fields. We present findings that characterize the degradation of the phase structure of ballistic scattered light carrying orbital angular momentum (OAM) propagated through a dense scattering medium over distances of up to 20 m. We present a numerical channel modeling approach that can predict the scattering behavior at extended distances, which indicates that there is a strong mode-dependent variance in cross talk from the interaction of beams that carry OAM with randomly displaced scattering particles. These results present an effect that could allow the use of OAM modes to enhance particulate size sensors and could potentially lead to the development of novel tools for monitoring particles in underwater or free-space optical channels