Objective

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Freeform deformation techniques of curves and surfaces have received considerable attention recently with the rapid development of geometric modeling and computer animation. A new local deformation algorithm for curves based on progressive iterative approximation (PIA) and dominant point methods is proposed in this study to acquire interesting and lifelike deformation effects. The new deformation method not only produces various deformation effects but also possesses desirable properties

such as flexibility and convergence

given the PIA method.

Method

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First

the initial deformation curves are obtained using the PIA or least squares PIA method. Second

the dominant points

which include the maximum local curvature points

and two end points are selected from the initial control points by calculating and comparing the curvatures that correspond to the control points. In this phase

we detect the maximum local curvature points using the rule that the curvature of a point must be larger than the curvatures of its neighboring points. Thus

the maximum local curvature points can be selected as the dominant points. Then

an extension rule is constructed on the region expected to be deformed. That is

we extend this region along the curve until it satisfies the two closest dominant points after selecting the region for deformation in accordance with real requirements. Thus

we can obtain a segment that is bounded by two dominant points. We classify the situation into two categories using the abovementioned extension rule on the basis of the number of dominant points in the obtained segment. The control points

which will be adjusted subsequently

are selected in accordance with the dominant points and the shape information of the curves. If the region that is prepared for deformation contains a dominant point

then three dominant points in the segment will be obtained after applying such extension rule. The dominant point in the middle is selected for subsequent adjustment. If the region that is prepared for deformation does not contain any dominant point

then only two dominant points in the segment will be obtained after extension. We select a control point in accordance with the shape information of the curve

which is useful in handling several complex deformation problems. In this situation

we first calculate the shape parameter for each control point in the obtained segment. The shape parameter represents the complexity of the curve and indicates the difference between two adjacent segments. Second

the control point that has the smallest shape parameter is selected for subsequent adjustment after comparing these parameters. We call this procedure the dominant point method. Moreover

if more than one dominant point in the region is expected to be deformed

then we can split the segment in accordance with the distribution of dominant points to ensure that each segment contains less than one dominant point. Then

we can use the abovementioned dominant point method to select the control points. Finally

local progressive iterative approximation (LPIA) method is adopted to generate the final curves after local deformation.

Result

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The proposed deformation method selects the control points on the basis of the complexity of the shapes of the curves. The deformation method is convergent

can be executed flexibly

and can highlight the features of the deformed regions through local iteration because we use the LPIA method to fit the data set after adjustment. Numerical examples

such as teapot

face contour

and hand

show that the proposed method can obtain favorable deformation effects through the B-spline basis

which is the most commonly used basis in geometric design and exhibits excellent local properties. Specifically

the teapot mouth is stretched by adjusting the selected control point. The lips

eyebrows

and earlobes of the face contour are deformed by using the deformation algorithm to generate a fascinating face. The fingers are also stretched to make the hand natural. We also demonstrate the distortion

which occurs when we do not use the deformation method proposed in this study

as illustrated in the teapot example. We can clearly observe that

if we do not adjust the control points generated by the algorithm

then the curve after deformation will be distorted and lack reality. Furthermore

this algorithm can be used repeatedly to generate the global

local

periodic

and elastic deformation effects.

Conclusion

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This study mainly focuses on applying the PIA method to the local curve deformations. First

we discuss the PIA method

which presents an intuitive and straightforward approach to fitting data points and provides flexibility for shape control in data fitting. Second

we introduce the notion of dominant points into the curve deformations. Finally

we propose a new deformation method on the basis of the PIA and dominant point methods by combining the two techniques. The algorithm not only possesses the properties of convergence and stability through the PIA method but also produces various positive deformation effects by selecting dominant points. A user must only select the regions expected to be deformed during the implementation of the deformation method and determine the deformation scales in accordance with his/her requirements

thus guaranteeing the interactivity of this algorithm. In summary

the proposed method significantly enriches the deformation effects of curves.