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Conference Papers Year : 2021

Visual Tracking of Deforming Objects Using Physics-based Models

Abstract

In this paper, we propose a framework for tracking the deformation of soft objects using a RGB-D camera by utilizing the physically-based model of the considered object. A coarse, 3D template of the object being tracked is the only prior information required by the proposed method. The proposed approach does not rely on the accurate knowledge of the material properties of the object being tracked. In this paper, we integrate computer vision based tracking methodology with physical model based deformation representation without requiring expensive numerical optimization for minimizing nonlinear error terms. The proposed approach enables deformation tracking by joint minimization of a geometric error and a direct photometric intensity error while utilizing co-rotational Finite Element Method (FEM) as the underlying deformation model. The proposed method has been validated both on synthetic data (with groundtruth) and real data.
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Dates and versions

hal-03179253 , version 1 (24-03-2021)

Identifiers

  • HAL Id : hal-03179253 , version 1

Cite

Agniva Sengupta, Alexandre Krupa, Eric Marchand. Visual Tracking of Deforming Objects Using Physics-based Models. ICRA 2021 - IEEE International Conference on Robotics and Automation, May 2021, Xi'an, China. pp.14178-14184. ⟨hal-03179253⟩
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