Two-view curve reconstruction based on the snake model

Cai, Yu; Su, Zhixun; Li, Zhilong; Sun, Runyuan; Liu, Xiuping; Zhao, Yuan-di

doi:10.1016/j.cam.2011.07.020

Cited by 8 publications

(9 citation statements)

References 6 publications

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“…The camera pixel coordinates of the particles were obtained by iteratively/repeatedly applying a Gaussian blur filter followed by threshold filtering, which removed the plasma column data and resulted in single-pixel sized particles. For the reconstruction of the plasma column, we adapted an approach based on the deformation of the so-called snake model; for a similar approach, see Cai et al 38 For validation purposes, we compared the projections of the reconstructions with the experimental data. From this, we concluded that for the present data, an average uncertainty of 0.13 mm can be achieved.…”

mentioning

confidence: 99%

Measurements of 3D slip velocities and plasma column lengths of a gliding arc discharge

Zhu

Gao

Ehn

et al. 2015

Applied Physics Letters

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A non-thermal gliding arc discharge was generated at atmospheric pressure in an air flow. The dynamics of the plasma column and tracer particles were recorded using two synchronized high-speed cameras. Whereas the data analysis for such systems has previously been performed in 2D (analyzing the single camera image), we provide here a 3D data analysis that includes 3D reconstructions of the plasma column and 3D particle tracking velocimetry based on discrete tomography methods. The 3D analysis, in particular, the determination of the 3D slip velocity between the plasma column and the gas flow, gives more realistic insight into the convection cooling process. Additionally, with the determination of the 3D slip velocity and the 3D length of the plasma column, we give more accurate estimates for the drag force, the electric field strength, the power per unit length, and the radius of the conducting zone of the plasma column.

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confidence: 99%

Measurements of 3D slip velocities and plasma column lengths of a gliding arc discharge

Zhu

Gao

Ehn

et al. 2015

Applied Physics Letters

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“…The resulting curve is shown in (f)-(h) and we see that it can well match the input data in both views. Meanwhile, the methods of predecessors (such as [10,11]) will fail when handling the input data, since the original data in the view Fig. 10(c) does not offer enough information to constraint the shape of the resulting curve.…”

Section: Results and Examplesmentioning

confidence: 99%

“…The external energy measures the closeness between the space curve and the input data points [10]. It can be represented as…”

Section: Formulation Of the Problemmentioning

confidence: 99%

“…According to the above analysis, the weight for each point should be cos À 1 θ, where θ is the angle between the space curve and the projection plane around that point. Also, we use the SDM method [13,10] for measuring the error term so as to improve convergence rates. Then the energy function can be rewritten as…”

Section: Energy Function Minimizationmentioning

confidence: 99%

“…Martinsson et al [9] introduced an iterative framework of control point insertion, so as to successively reconstruct 3D NURBS curves. Cai et al [10] reconstructed space NURBS curves based on deformation of the snake model, such that the necessity of matching was relaxed. Saini et al [11] used NURBS-snake models to construct a planar NURBS curve from each image, and generated the control points of space curves by stereo triangulation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

3D B-spline curve construction from orthogonal views with self-overlapping projection segments

Yang

Yong

Shi

et al. 2016

Computers & Graphics

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Two view NURBS reconstruction based on GACO model

Saini

Kumar

Singh

et al. 2021

Complex Intell. Syst.

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The key job here in the presented work is to investigate the performance of Generalized Ant Colony Optimizer (GACO) model in order to evolve the shape of three dimensional free-form Non Uniform Rational B-Spline (NURBS) curve using stereo (two) views. GACO model is a blend of two well known meta-heuristic optimization algorithms known as Simple Ant Colony and Global Ant Colony Optimization algorithms. Basically, the work talks about the solution of NURBS-fitting based reconstruction process. Therefore, GACO model is used to optimize the NURBS parameters (control points and weights) by minimizing the weighted least-square errors between the data points and the fitted NURBS curve. The algorithm is applied by first assuming some pre-fixed values of NURBS parameters. The experiments clearly show that the optimization procedure is a better option in a case where good initial locations of parameters are selected. A detailed experimental analysis is given in support of our algorithm. The implemented error analysis shows that the proposed methodology perform better as compared to the conventional methods.

show abstract

Two-view curve reconstruction based on the snake model

Cited by 8 publications

References 6 publications

Measurements of 3D slip velocities and plasma column lengths of a gliding arc discharge

Measurements of 3D slip velocities and plasma column lengths of a gliding arc discharge

3D B-spline curve construction from orthogonal views with self-overlapping projection segments

Two view NURBS reconstruction based on GACO model

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