research-article

Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks

Authors:

Jonathan Tompson,

Ken PerlinAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 33, Issue 5

Article No.: 169, Pages 1 - 10

https://doi.org/10.1145/2629500

Published: 23 September 2014 Publication History

Abstract

We present a novel method for real-time continuous pose recovery of markerless complex articulable objects from a single depth image. Our method consists of the following stages: a randomized decision forest classifier for image segmentation, a robust method for labeled dataset generation, a convolutional network for dense feature extraction, and finally an inverse kinematics stage for stable real-time pose recovery. As one possible application of this pipeline, we show state-of-the-art results for real-time puppeteering of a skinned hand-model.

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Cited By

Roumaissa BMohamed Chaouki B(2025)Deep learning based on hand pose estimation methods: a systematic literature reviewMultimedia Tools and Applications10.1007/s11042-025-20704-6Online publication date: 22-Feb-2025
https://doi.org/10.1007/s11042-025-20704-6
Do VLe V(2025)Fine-Tuning of 3D Hand Pose Estimation on HOI4D Dataset by Convolutional Neural NetworksOptimization and Data Science in Industrial Engineering10.1007/978-3-031-81455-6_11(171-188)Online publication date: 26-Jan-2025
https://doi.org/10.1007/978-3-031-81455-6_11
Hong‐qin XYuan‐yuan Z(2025)Advanced Gesture Recognition Method Based on Fractional Fourier Transform and Relevance Vector Machine for Smart Home AppliancesComputer Animation and Virtual Worlds10.1002/cav.7001136:1Online publication date: 30-Jan-2025
https://doi.org/10.1002/cav.70011
Show More Cited By

Index Terms

Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks
1. Computing methodologies
  1. Computer graphics
    1. Animation
    2. Graphics systems and interfaces
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices
      1. Graphics input devices

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 33, Issue 5

August 2014

152 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2672594

Editor:
Julie Dorsey
Yale University

Issue’s Table of Contents

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 September 2014

Accepted: 01 March 2014

Revised: 01 January 2014

Received: 01 August 2013

Published in TOG Volume 33, Issue 5

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Cited By

Roumaissa BMohamed Chaouki B(2025)Deep learning based on hand pose estimation methods: a systematic literature reviewMultimedia Tools and Applications10.1007/s11042-025-20704-6Online publication date: 22-Feb-2025
https://doi.org/10.1007/s11042-025-20704-6
Do VLe V(2025)Fine-Tuning of 3D Hand Pose Estimation on HOI4D Dataset by Convolutional Neural NetworksOptimization and Data Science in Industrial Engineering10.1007/978-3-031-81455-6_11(171-188)Online publication date: 26-Jan-2025
https://doi.org/10.1007/978-3-031-81455-6_11
Hong‐qin XYuan‐yuan Z(2025)Advanced Gesture Recognition Method Based on Fractional Fourier Transform and Relevance Vector Machine for Smart Home AppliancesComputer Animation and Virtual Worlds10.1002/cav.7001136:1Online publication date: 30-Jan-2025
https://doi.org/10.1002/cav.70011
Wan XJu JTang JLin MRao NChen DLiu TLi JBian FXiong N(2024)MPCTrans: Multi-Perspective Cue-Aware Joint Relationship Representation for 3D Hand Pose Estimation via Swin TransformerSensors10.3390/s2421702924:21(7029)Online publication date: 31-Oct-2024
https://doi.org/10.3390/s24217029
Kim YSo JHwang CCheng WKo J(2024)An Energy-Efficient Dynamic Feedback Image Signal Processor for Three-Dimensional Time-of-Flight SensorsSensors10.3390/s2421691824:21(6918)Online publication date: 28-Oct-2024
https://doi.org/10.3390/s24216918
Yu SWang YChen LZhang XLi J(2024)3D hand pose and mesh estimation via a generic Topology-aware Transformer modelFrontiers in Neurorobotics10.3389/fnbot.2024.139565218Online publication date: 3-May-2024
https://doi.org/10.3389/fnbot.2024.1395652
Shin JHasan MMiah ASuzuki KHirooka K(2024)Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning ClassificationComputer Modeling in Engineering & Sciences10.32604/cmes.2023.046334139:3(2605-2625)Online publication date: 2024
https://doi.org/10.32604/cmes.2023.046334
Abd Al-Latief SYussof SAhmad AKhadim S(2024)Deep Learning for Sign Language Recognition: A Comparative ReviewJournal of Smart Internet of Things10.2478/jsiot-2024-00062024:1(77-116)Online publication date: 15-Jun-2024
https://doi.org/10.2478/jsiot-2024-0006
Pu MLim MChong CCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Siformer: Feature-isolated Transformer for Efficient Skeleton-based Sign Language RecognitionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681578(9387-9396)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681578
Zhao WHu HZhou WLi LLi H(2024)Exploiting Spatial-Temporal Context for Interacting Hand Reconstruction on Monocular RGB VideoACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363970720:6(1-18)Online publication date: 8-Mar-2024
https://dl.acm.org/doi/10.1145/3639707
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