arXiv subjects

Giancarlo Pereira

Publications and source records attributed to Giancarlo Pereira.

3 recordsLinked to original sources

arXiv2025

LookUp3D: Data-Driven 3D Scanning

High speed, high-resolution, and accurate 3D scanning would open doors to many new applications in graphics, robotics, science, and medicine by enabling the accurate scanning of deformable objects during interactions. Past attempts to use structured light, time-of-flight, and stereo in high-speed settings have usually required tradeoffs in resolution or inaccuracy. In this paper, we introduce a method that enables, for the first time, 3D scanning at 450 frames per second at 1~Megapixel, or 1,450 frames per second at 0.4~Megapixel in an environment with controlled lighting. The key idea is to use a per-pixel lookup table that maps colors to depths, which is built using a linear stage. Imperfections, such as lens-distortion and sensor defects are baked into the calibration. We describe our method and test it on a novel hardware prototype. We compare the system with both ground-truth geometry as well as commercially available dynamic sensors like the Microsoft Kinect and Intel Realsense. Our results show the system acquiring geometry of objects undergoing high-speed deformations and oscillations and demonstrate the ability to recover physical properties from the reconstructions.

cs.CV↗

arXiv2025

Cavity-altered superconductivity

Is it feasible to alter the ground state properties of a material by engineering its electromagnetic environment? Inspired by theoretical predictions, experimental realizations of such cavity-controlled properties without optical excitation are beginning to emerge. Here, we devised and implemented a novel platform to realize cavity-altered materials. Single crystals of hyperbolic van der Waals (vdW) compounds provide a resonant electromagnetic environment with enhanced density of photonic states and prominent mode confinement. We interfaced hexagonal boron nitride (hBN) with the molecular superconductor $κ$-(BEDT-TTF)$_2$Cu[N(CN)$_2$]Br ($κ$-ET). The frequencies of infrared (IR) hyperbolic modes of hBN match the IR-active carbon-carbon stretching molecular resonance of ($κ$-ET) implicated in superconductivity. Nano-optical data supported by first-principles molecular Langevin dynamics simulations confirm the presence of resonant coupling between the hBN hyperbolic cavity modes and the carbon-carbon stretching mode in ($κ$-ET). Meissner effect measurements via magnetic force microscopy demonstrate a strong suppression of superfluid density near the hBN/($κ$-ET) interface. Non-resonant control heterostructures, including RuCl$_3$/($κ$-ET) and hBN/$\text{Bi}_2\text{Sr}_2\text{CaCu}_2\text{O}_{8+x}$, do not display the superfluid suppression. These observations suggest that hBN/($κ$-ET) realizes a cavity-altered superconducting ground state. Our work highlights the potential of dark cavities devoid of external photons for engineering electronic ground state properties of complex quantum materials.

cond-mat.supr-con↗

arXiv2024

Towards Data-Informed Interventions: Opportunities and Challenges of Street-level Multimodal Sensing

Over the past decades, improvements in data collection hardware coupled with novel artificial intelligence algorithms have made it possible for researchers to understand urban environments at an unprecedented scale. From local interactions between actors to city-wide infrastructural problems, this new data-driven approach enables a more informed and trustworthy decision-making process aiming at transforming cities into safer and more equitable places for living. This new moment unfolded new opportunities to understand various phenomena that directly impact how accessible cities are to heterogeneous populations. Specifically, sensing localized physical interactions among actors under different scenarios can drive substantial interventions in urban environments to make them safer for all. In this manuscript, we list opportunities and associated challenges to leverage street-level multimodal sensing data to empower domain experts in making more informed decisions and, ultimately, supporting a data-informed policymaking framework. The challenges presented here can motivate research in different areas, such as computer vision and human-computer interaction, to support cities in growing more sustainably.

cs.HC↗