594 research outputs found
A framework for real-time hand gesture recognition in uncontrolled environments with partition matrix model based on hidden conditional random fields
Get PDFThe main obstructions of making hand gesture recognition methods robust in real-world applications are the challenges from the uncontrolled environments, including: gesturing hand out of the scene, pause during gestures, complex background, skin-coloured regions moving in background, performers wearing short sleeve and face overlapping with hand. Therefore, a framework for real-time hand gesture recognition in uncontrolled environments is proposed in this paper. A novel tracking scheme is proposed to track multiple hand candidates in unconstrained background, and a weighting model for gesture classification based on Hidden Conditional Random Fields which takes trajectories of multiple hand candidates under different frame rates into consideration is also introduced. The framework achieved invariance under change of scale, speed and location of the hand gestures. The Experimental results of the proposed framework on Palm Graffiti Digits database and Warwick Hand Gesture database show that it can perform well in uncontrolled environments
Real-time hand gesture recognition for uncontrolled environments using adaptive SURF tracking and hidden conditional random fields
Get PDFChallenges from the uncontrolled environments are the main difficulties in making hand gesture recognition methods robust in real-world scenarios. In this paper, we propose a real-time and purely vision-based method for hand gesture recognition in uncontrolled environments. A novel tracking method is introduced to track multiple hand candidates from the first frame. The movement directions of all hand candidates are extracted as trajectory features. A modified HCRF model is used to classify gestures. The proposed method can survive challenges including: gesturing hand out of the scene, pause during gestures, complex background, skin-coloured regions moving in background, performers wearing short sleeve and face overlapping with hand. The method has been tested on Palm Graffiti Digits database and Warwick Hand Gesture database. Experimental results show that the proposed method can perform well in uncontrolled environments
A Unified Framework for Vertical States Estimation:Data-Driven Approach Incorporating Uncertainty
No full textAccurate and real-time knowledge of vertical states plays a critical role in vehicular safety and comfort. It contributes to enhanced cornering performance, detailed modeling of vehicle dynamics, and effective implementation of control strategies for numerous active safety systems, especially semi-active and active suspensions. For this purpose, this study aims to estimate three key dynamical states that are impractical to acquire via direct measurements: tire vertical force, road profile, and unsprung mass velocity. A unified framework tailored to the context of vertical dynamics is proposed, leveraging a state-of-the-art multivariate prediction model known as Neural Basis Expansion Analysis for Time Series (N-BEATS). This model uses existing in-vehicle signals and is trained using data from a simulation platform with a high-fidelity vehicle model. Additionally, the model provides an uncertainty interval of its estimation rather than a single value. Test results reveal that N-BEATS exhibits good tracking performance, outperforming Long Short-Term Memory (LSTM) in terms of estimation errors and inference speed. Finally, we highlight extra functionalities of the developed virtual sensor such as road quality classification and the consistency of the temporal-frequency content between predicted signals and the ground truth labels
Quantitative imaging of advanced nanostructured materials with scattering-type scanning near field optical microscopy
No full textScattering-type Scanning Near Field Optical Microscopy (s-SNOM) has been demonstrated as a valuable tool for revealing important properties of materials at nanoscale. Recent proof-of-concept experiments have shown that, among others, s-SNOM can provide quantitative information on the real and imaginary parts of the dielectric function, and hence of intrinsic optical properties of materials and biological samples. In this work we further explored these capabilities in several experiments dealing with microcapsules for drug delivery, ultra-thin optical coatings with tunable color properties, and two types of nanoparticles with important applications in energy storage and conversion, or biosensing and theranostics
Semi-autonomous Robotic Disassembly Enhanced by Mixed Reality
Get PDFIn this study, we introduce "SARDiM,"a modular semi-autonomous platform enhanced with mixed reality for industrial disassembly tasks. Through a case study focused on EV battery disassembly, SARDiM integrates Mixed Reality, object segmentation, teleoperation, force feedback, and Variable Autonomy. Utilising the ROS, Unity, and MATLAB platforms, alongside a joint impedance controller, SARDiM facilitates teleoperated disassembly. The approach combines FastSAM for real-time object segmentation, generating data which is subsequently processed through a cluster analysis algorithm to determine the centroid and orientation of the components, categorizing them by size and disassembly priority. This data guides the MoveIt platform in trajectory planning for the Franka Robot arm. SARDiM provides the capability to switch between two teleoperation modes: 1) manual and 2) semi-autonomous with Variable Autonomy. Each was evaluated using four different Interface Methods (IM): 1) direct view, 2) monitor feed, 3) mixed reality with monitor feed, and 4) point cloud mixed reality. Evaluations across the eight IMs demonstrated a 40.61% decrease in joint limit violations using Mode 2. Moreover, Mode 2-IM4 outperformed Mode 1-IM1 by achieving a 2.33%-time reduction while considerably increasing safety, making it optimal for operating in hazardous environments at a safe distance, with the same ease of use as teleoperation with a direct view of the environment.</p
Full‐Control and Switching of Optical Fano Resonance by Continuum State Engineering
No full textAbstract Fano resonance, known for its unique asymmetric line shape, has gained significant attention in photonics, particularly in sensing applications. However, it remains difficult to achieve controllable Fano parameters with a simple geometric structure. Here, a novel approach of using a thin‐film optical Fano resonator with a porous layer to generate entire spectral shapes from quasi‐Lorentzian to Lorentzian to Fano is proposed and experimentally demonstrated. The glancing angle deposition technique is utilized to create a polarization‐dependent Fano resonator. By altering the linear polarization between s‐ and p‐polarization, a switchable Fano device between quasi‐Lorentz state and negative Fano state is demonstrated. This change in spectral shape is advantageous for detecting materials with a low‐refractive index. A bio‐particle sensing experiment is conducted that demonstrates an enhanced signal‐to‐noise ratio and prediction accuracy. Finally, the challenge of optimizing the film‐based Fano resonator due to intricate interplay among numerous parameters, including layer thicknesses, porosity, and materials selection, is addressed. The inverse design tool is developed based on a multilayer perceptron model that allows fast computation for all ranges of Fano parameters. The method provides improved accuracy of the mean validation factor (MVF = 0.07, q‐q') compared to the conventional exhaustive enumeration method (MVF = 0.37)
Dual-infinite coordination polymer-engineered nanomedicines for dual-ion interference-mediated oxidative stress-dependent tumor suppression
No full textRecently, nanomedicine design has shifted from simple nanocarriers to nanodrugs with intrinsic antineoplastic activities for therapeutic performance optimization. In this regard, degradable nanomedicines containing functional inorganic ions have blazed a highly efficient and relatively safe ion interference paradigm for cancer theranostics. Herein, given the potential superiorities of infinite coordination polymers (ICPs) in degradation peculiarity and functional integration, a state-of-the-art dual-ICP-engineered nanomedicine is elaborately fabricated via integrating ferrocene (Fc) ICPs and calcium-tannic acid (Ca-TA) ICPs. Thereinto, Fc ICPs, and Ca-TA ICPs respectively serve as suppliers of ferrous iron ions (Fe2+) and calcium ions (Ca2+). After the acid-responsive degradation of ICPs, released TA from Ca-TA ICPs facilitated the conversion of released ferric iron (Fe3+) from Fc ICPs into highly active Fe2+. Owing to the dual-path oxidative stress and neighboring effect mediated by Fe2+ and Ca2+, such a dual-ICP-engineered nanomedicine effectively induces dual-ion interference against triple-negative breast cancer (TNBC). Therefore, this work provides a novel antineoplastic attempt to establish ICP-engineered nanomedicines and implement ion interference-mediated synergistic therapy.
Double-punch" strategy against triple-negative breast cancer via a synergistic therapy of magneto-mechanical force enhancing NIR-II hypothermal ablation
No full textTriple-negative breast cancer (TNBC) is a form of breast cancer that is more aggressive and harder to treat than others, with a higher probability of relapse. Its nefarious capabilities for migrating and invading other parts of the body together with the current lack of clinically established effective therapies account for a low survival rate. In this work, we demonstrate the in-tandem use of two complementary therapeutic routes to effectively combat TNBC. A versatile magnetic-photothermal converter (MPC) consisting of zinc-doped ferrite nanoparticles and polyethene glycol, is shown to display excellent therapeutic efficiency, being capable to fight TNBC via two distinct routes: magneto-mechanical force (MMF) and near-infrared-II (NIR-II) hypothermal ablation. The combined use of these two complementary and synergistic therapies, which are less aggressive to the human body compared to conventional chemotherapeutic approaches, results in the splendid suppression of TNBC migration and invasion. Remotely controlling the MPCs by an external magnetic field, results in cellular MMF effects that cause direct mechanical destruction to the cancer cell membrane, leading to its necrosis. Further-more, the MMF disrupts intracellular lysosomes, thereby triggering the release of large amounts of protein hy-drolases, which induce intracellular oxidative stress, and accelerate the induction of apoptosis. Complementing the therapeutic approach based on MMF, the excellent photothermal performance of the MPC in the NIR-II region (1064 nm) is exploited to enable effective hypothermal ablation of the tumours, which can be achieved in deep tissue layers. The proposed multifunctional nanocomposites, together with the demonstrated "double-punch" therapeutic approach, hold significant potential to pave the way for future cutting-edge weapons against the dreadful TNBC.
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