3D Hand Pose Estimation Based on Five-Layer Ensemble CNN [PDF]
Sensors, 2021 Estimating accurate 3D hand pose from a single RGB image is a highly challenging problem in pose estimation due to self-geometric ambiguities, self-occlusions, and the absence of depth information. To this end, a novel Five-Layer Ensemble CNN (5LENet) is
Lili Fan, Hong Rao, Wenji Yang
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SARN: Shifted Attention Regression Network for 3D Hand Pose Estimation [PDF]
Bioengineering, 2023 Hand pose estimation (HPE) plays an important role during the functional assessment of the hand and in potential rehabilitation. It is a challenge to predict the pose of the hand conveniently and accurately during functional tasks, and this limits the ...
Chenfei Zhu +4 more
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Single Shot Corrective CNN for Anatomically Correct 3D Hand Pose Estimation [PDF]
Frontiers in Artificial Intelligence, 2022 Hand pose estimation in 3D from depth images is a highly complex task. Current state-of-the-art 3D hand pose estimators focus only on the accuracy of the model as measured by how closely it matches the ground truth hand pose but overlook the resulting ...
Joseph H. R. Isaac +3 more
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Survey on depth and RGB image-based 3D hand shape and pose estimation
Virtual Reality & Intelligent Hardware, 2021 The field of vision-based human hand three-dimensional (3D) shape and pose estimation has attracted significant attention recently owing to its key role in various applications, such as natural humancomputer interactions.
Lin Huang +5 more
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MPCTrans: Multi-Perspective Cue-Aware Joint Relationship Representation for 3D Hand Pose Estimation via Swin Transformer [PDF]
SensorsThe objective of 3D hand pose estimation (HPE) based on depth images is to accurately locate and predict keypoints of the hand. However, this task remains challenging because of the variations in hand appearance from different viewpoints and severe ...
Xiangan Wan +9 more
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Hand gesture 3D pose estimation method based on swin transformer and CNN [PDF]
Scientific ReportsExisting gesture pose estimation methods commonly exhibit limitations such as singular feature extraction for hand characteristics and the neglect of long-range topological relationships between joints, thus restricting their prediction accuracy.
Rong Dang, Gang Feng
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Hand–Object Pose Estimation Based on Anchor Regression from a Single Egocentric Depth Image [PDF]
SensorsTo precisely understand the interaction behaviors of humans, a computer vision system needs to accurately acquire the poses of the hand and its manipulated object. Vision-based hand–object pose estimation has become an important research topic.
Jingang Lin +3 more
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A deep learning-based method combines manual and non-manual features for sign language recognition [PDF]
Scientific ReportsThis research examines the advantages of utilizing 3D hand skeletal information for sign language identification from RGB videos within a cutting-edge, multi-stream deep learning recognition framework.
Haifa Harrouch +3 more
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Research on Deep Learning-Based Human–Robot Static/Dynamic Gesture-Driven Control Framework [PDF]
SensorsFor human–robot gesture-driven control, this paper proposes a deep learning-based approach that employs both static and dynamic gestures to drive and control robots for object-grasping and delivery tasks. The method utilizes two-dimensional Convolutional
Gong Zhang +5 more
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Video-based quantification of hand postural tremor without external references. Integrating postural tremor quantification into visionMD [PDF]
npj Parkinson's DiseaseWe developed a method to quantify hand postural tremor amplitude and frequency from standard videos without external calibration. Using iris-based scaling and deep-learning models for 3D pose estimation and hand tracking, the automatic approach ...
Diego L. Guarín
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