Non‐Rigid Surface Matching and Its Application to Scoliosis Modelling

Ang, Kim-Siang; Mitchell, Harvey

doi:10.1111/j.1477-9730.2010.00581.x

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…If the occurrence of body movement is frequent and its amplitudes are significant, this method is not sufficient to accurately measure the displacements or volume of the thoraco-abdominal region. Recently, a non-rigid surface matching method based on least squares estimation was proposed, where the authors measured the deformation due to scoliotic changes of the patient's back (Ang and Mitchell 2010). Since the deformation of the back due to the breathing is minimal, the study did not investigate the model that is capable of measuring the breathing related deformations.…”

Section: Introductionmentioning

confidence: 99%

Real-time 3D visualization of the thoraco-abdominal surface during breathing with body movement and deformation extraction

2015

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Real-time 3D visualization of the breathing displacements can be a useful diagnostic tool in order to immediately observe the most active regions on the thoraco-abdominal surface. The developed method is capable of separating non-relevant torso movement and deformations from the deformations that are solely related to breathing. This makes it possible to visualize only the breathing displacements. The system is based on the structured laser triangulation principle, with simultaneous spatial and color data acquisition of the thoraco-abdominal region. Based on the tracking of the attached passive markers, the torso movement and deformation is compensated using rigid and non-rigid transformation models on the three-dimensional (3D) data. The total time of 3D data processing together with visualization equals 20 ms per cycle.In vitro verification of the rigid movement extraction was performed using the iterative closest point algorithm as a reference. Furthermore, a volumetric evaluation on a live subject was performed to establish the accuracy of the rigid and non-rigid model. The root mean square deviation between the measured and the reference volumes shows an error of ±0.08 dm(3) for rigid movement extraction. Similarly, the error was calculated to be ±0.02 dm(3) for torsional deformation extraction and ±0.11 dm(3) for lateral bending deformation extraction. The results confirm that during the torso movement and deformation, the proposed method is sufficiently accurate to visualize only the displacements related to breathing. The method can be used, for example, during the breathing exercise on an indoor bicycle or a treadmill.

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Section: Introductionmentioning

confidence: 99%

Real-time 3D visualization of the thoraco-abdominal surface during breathing with body movement and deformation extraction

2015

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“…The use of consumer cameras for accurate photogrammetric applications is reported by, for example, Chandler et al (2005) who examined the potential of low‐cost digital cameras for close‐range surface measurement using feature‐based image matching methods, by extracting digital elevation models (DEMs) and comparing accuracies between three low‐cost consumer‐grade digital cameras. Other interesting research efforts are concentrated on the development of new and more accurate calibration (Chong et al, 2009) and matching techniques (Ang and Mitchell, 2010), especially for medical applications.…”

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confidence: 99%

Digital close range photogrammetry for 3D body scanning for custom‐made garments

Percoco

2011

The Photogrammetric Record

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Among several biometric applications, one of those currently attracting great interest is the possibility of carrying out 3D digitisation of human individuals to analyse their physical characteristics. These characteristics can be used for several purposes, such as security, medicine and tailoring for custom‐made clothing. In recent years, although the development of online 3D scanning systems has been accelerating fast, little work has been devoted to offline systems, which would be particularly suitable for the textile and clothing industries. In the present research the author presents a specially designed low‐cost offline 3D body digitiser, based on digital close range photogrammetry. A specially designed photogrammetric 3D scanner of the human body is presented, featuring automatic image processing procedures. The scanning system consists of eight cameras with a resolution of 5 megapixels, equipped with 16 mm wide‐angle lenses; there are four white‐light illuminators, of 100 W each. Tests on a tailor’s dummy and on whole human bodies are reported, demonstrating the usefulness of the technique for textile applications. The digitisations performed on human bodies generally yield worse results than the corresponding ones on the dummy, and full body digitisations are worse than corset digitisations owing to the lower point density and to target distortion. Nevertheless, the results are satisfactory for tailoring applications that do not require high accuracies.

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