Top-down model fitting for hand pose recovery in sequences of depth images-Reference-Cited by-同舟云学术

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Top-down model fitting for hand pose recovery in sequences of depth images

Published:2018-11 Issue: Volume:79 Page:63-75
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Madadi Meysam^ORCID,Escalera Sergio,Carruesco Alex,Andujar Carlos,Baró Xavier,Gonzàlez Jordi

Funder

MINECO/FEDER, UE

CERCA Programme/Generalitat de Catalunya

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference44 articles.

1. Bilinear spatiotemporal basis models;Akhter;ACM Trans. Graph. (TOG),2012

2. Shape matching and object recognition using shape contexts;Belongie;PAMI,2002

3. A collaborative filtering approach to real-time hand pose estimation;Choi,2015

4. Surround-screen projection-based virtual reality: the design and implementation of the CAVE;Cruz-Neira,1993

5. The CAVE: audio visual experience automatic virtual environment;Cruz-Neira;Commun. ACM,1992

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3. Learning End-User Customized Mid-Air Hand Gestures Using a Depth Image Sensor;IEEE Sensors Journal;2022-09-01

4. TravelNet: Self-supervised Physically Plausible Hand Motion Learning from Monocular Color Images;2021 IEEE/CVF International Conference on Computer Vision (ICCV);2021-10

5. End‐to‐end global to local convolutional neural network learning for hand pose recovery in depth data;IET Computer Vision;2021-08-12

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