Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects

Sun, Walter; Çetin, Müjdat; Chan, Raymond C. K.; Willsky, Alan S.

doi:10.1109/tip.2008.2004638

Cited by 13 publications

(9 citation statements)

References 41 publications

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“…In computer vision applications, such as human tracking and medical imaging, level set methods have been used successfully in tracking deformable objects (Sethian, 1997;Cremers, 2006). For example, Sun et al (2008) recursively segmented deformable objects across a sequence of frames using a low-dimensional modal representation and applied their technique to left ventricular segmentation across a cardiac cycle. The dynamics are represented using a distance level set function, whose representation is simplified using principal component analysis (PCA).…”

Section: Level Set Methodsmentioning

confidence: 99%

Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review

et al. 2020

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Manipulation of deformable objects has given rise to an important set of open problems in the field of robotics. Application areas include robotic surgery, household robotics, manufacturing, logistics, and agriculture, to name a few. Related research problems span modeling and estimation of an object's shape, estimation of an object's material properties, such as elasticity and plasticity, object tracking and state estimation during manipulation, and manipulation planning and control. In this survey article, we start by providing a tutorial on foundational aspects of models of shape and shape dynamics. We then use this as the basis for a review of existing work on learning and estimation of these models and on motion planning and control to achieve desired deformations. We also discuss potential future lines of work.

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Section: Level Set Methodsmentioning

confidence: 99%

Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review

et al. 2020

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“…FEMs numerically solve coupled constituents equations defined over object meshes for object deformations as a function of applied boundary conditions. FEM methods are typically prohibitively computationally expensive to run online and require careful system identification [4], [35], [36]. Particle models approximate objects as a set of particles related to each other by constitutive laws.…”

Section: E Dense Correspondencementioning

confidence: 99%

VIRDO: Visio-tactile Implicit Representations of Deformable Objects

Wi¹,

Florence²,

Zeng³

et al. 2022

Preprint

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Deformable object manipulation requires computationally efficient representations that are compatible with robotic sensing modalities. In this paper, we present VIRDO: an implicit, multi-modal, and continuous representation for deformable-elastic objects. VIRDO operates directly on visual (point cloud) and tactile (reaction forces) modalities and learns rich latent embeddings of contact locations and forces to predict object deformations subject to external contacts. Here, we demonstrate VIRDOs ability to: i) produce highfidelity cross-modal reconstructions with dense unsupervised correspondences, ii) generalize to unseen contact formations, and iii) state-estimation with partial visio-tactile feedback.

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“…Furthermore, the evolutions of endocardial and epicardial curves are coupled by an extra level-set constraint. The deformable models proposed in [ 106 , 107 ] and the level-set approaches presented in [ 108 , 109 ] incorporate the spatial–temporal LV activation as prior knowledge and track the epicardium/endocardium boundaries on SAX slices in a complete cycle. A typical tracking result is shown in Fig.…”

Section: Cardiac Segmentationmentioning

confidence: 99%

A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging

Peng

Lekadir

Gooya

et al. 2016

Magn Reson Mater Phy

239

147

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Cardiovascular magnetic resonance (CMR) has become a key imaging modality in clinical cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac chambers and great vessels. A wide range of CMR sequences have been developed to assess various aspects of cardiac structure and function, and significant advances have also been made in terms of imaging quality and acquisition times. A lot of research has been dedicated to the development of global and regional quantitative CMR indices that help the distinction between health and pathology. The goal of this review paper is to discuss the structural and functional CMR indices that have been proposed thus far for clinical assessment of the cardiac chambers. We include indices definitions, the requirements for the calculations, exemplar applications in cardiovascular diseases, and the corresponding normal ranges. Furthermore, we review the most recent state-of-the art techniques for the automatic segmentation of the cardiac boundaries, which are necessary for the calculation of the CMR indices. Finally, we provide a detailed discussion of the existing literature and of the future challenges that need to be addressed to enable a more robust and comprehensive assessment of the cardiac chambers in clinical practice.

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Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects

Cited by 13 publications

References 41 publications

Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review

Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review

VIRDO: Visio-tactile Implicit Representations of Deformable Objects

A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging

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