Results 41 to 50 of about 6,005,844 (276)
CFAM: Estimating 3D Hand Poses from a Single RGB Image with Attention
Applied Sciences, 2020 Precise 3D hand pose estimation can be used to improve the performance of human−computer interaction (HCI). Specifically, computer-vision-based hand pose estimation can make this process more natural.
Xianghan Wang +5 more
doaj +1 more source
Hand Pose Estimation in the Task of Egocentric Actions
IEEE Access, 2021 In this article we tackle the problem of hand pose estimation when the hand is interacting with various objects from egocentric viewpoint. This entails a frequent occlusion of parts of the hand by the object and also self-occlusions of the hand. We use a
Marek Hruz, Jakub Kanis, Zdenek Krnoul
doaj +1 more source
1st Place Solution of Egocentric 3D Hand Pose Estimation Challenge 2023 Technical Report:A Concise Pipeline for Egocentric Hand Pose Reconstruction [PDF]
, 2023 This report introduce our work on Egocentric 3D Hand Pose Estimation workshop. Using AssemblyHands, this challenge focuses on egocentric 3D hand pose estimation from a single-view image.
Zhou, Zhishan +7 more
core +1 more source
A Comprehensive Study on Deep Learning-Based 3D Hand Pose Estimation Methods
Applied Sciences, 2020 The field of 3D hand pose estimation has been gaining a lot of attention recently, due to its significance in several applications that require human-computer interaction (HCI).
Theocharis Chatzis +4 more
doaj +1 more source
The Self-Referenced DLR 3D-Modeler [PDF]
, 2009 In the context of 3-D scene modeling, this work aims at the accurate estimation of the pose of a close-range 3-D modeling device, in real-time and passively from its own images.
Hirzinger, Gerd +14 more
core +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Neural Hand Reconstruction Using A Single RGB Image
Virtual Reality & Intelligent Hardware, 2020 We present a neural hand reconstruction method for monocular 3D hand pose and shape estimation in this paper. Instead of directly representing hand with 3D data, a novel UV position map is introduced to represent hand pose and shape with 2D data, which ...
Mengcheng Li +5 more
doaj +1 more source
Recent Advances in 3D Object and Hand Pose Estimation
CoRR, 2020 3D object and hand pose estimation have huge potentials for Augmented Reality, to enable tangible interfaces, natural interfaces, and blurring the boundaries between the real and virtual worlds. In this chapter, we present the recent developments for 3D object and hand pose estimation using cameras, and discuss their abilities and limitations and the ...
openaire +3 more sources
DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation [PDF]
2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017 DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations of a hand given a depth map. Since its publication early 2015, it has been outperformed by several impressive works. Here we show that with simple improvements: adding ResNet layers, data augmentation, and better initial hand localization, we achieve better or ...
Oberweger, Markus, Lepetit, Vincent
openaire +4 more sources
Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis
Arthritis Care &Research, EarlyView.Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling +4 more
wiley +1 more source