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April 13, 2026Open Access

Can We Infer Object Pose Changes from Hand Movements?

Julien Berry Emmanuel Pietriga Olivier Chapuis Caroline Appert

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Key Points

The research aims to explore the relationship between hand movements and changes in object pose.
Analyzed hand movement kinematics using motion capture technology.
Developed algorithms for detecting and interpreting hand-object interactions.
Evaluated performance through experiments involving various object poses.
Found a strong correlation between hand movements and object pose changes.
Achieved high accuracy in predicting object pose using hand movement data.
Demonstrated feasibility of the approach for real-time applications.

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Implication

Demonstrates the ability to infer object pose changes based on hand movements, suggesting potential applications in robotics.

Abstract

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Cite This Study

Berry et al. (2026) studied this question.

synapsesocial.com/papers/69c8c35cde0f0f753b39e1ea https://doi.org/10.1145/3772318.3790384

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Keep reading

Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context:

1On the Utility of 3D Hand Poses for Action Recognition2024 · 13 citations
2Hands in action: real-time 3D reconstruction of hands in interaction with objectsOriginal Research · 2010 · 120 citations
3Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects2024 · 22 citations
4GRIP: Generating Interaction Poses Using Spatial Cues and Latent Consistency2024 · 21 citations
5Hand–Object Pose Estimation Based on Anchor Regression from a Single Egocentric Depth Image2025
6Forecasting Bimanual Object Manipulation Sequences from Unimanual Observations2024 · 2 citations
7GEARS: Local Geometry-Aware Hand-Object Interaction SynthesisOriginal Research · 2024 · 17 citations
8HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields2024 · 1 citations

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