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 Wysłany: Wto 2:16, 23 Lis 2010 Temat postu: tory burch white flats Adjustable multi-constraine |
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Adjustable multi-constrained Catmull-Clark Subdivision Surfaces
Limit point formula can be obtained '\may think that p \According to the above formula, consider adjusting the location of the interpolation methods to achieve peak due to P: \, ..., m-1) corresponding to the revised value of 8.1 Li '64m (m +5) p a (64m +273) Σ a Σ (23a ~ + +23 c ~)) If the target interpolation point P? and P \normal to n is' np; = 0, Ji p'np = 0 where: p \limit point; r ..., Ji ... are p \3.3 Based on similar smoothness constraint can be obtained despite the above constraints to meet the subdivision surface, but in many cases there will be not only smooth wrinkles and other phenomena, leading to limit surface quality is not high, it is necessary to deal with smoothing If the constraint in achieving the interpolation after smoothing processing will not only affect the accuracy of interpolation and reduces the efficiency of the algorithm, so a better approach is to consider in the process of interpolation smoothing problem, that is the culmination of disturbance in the control process, In the geometric constraints and constraints smoothing the adjustment to optimize the amount of control points. [11] proposed the interpolation based on similarity proved to be an effective way to achieve smooth interpolation, in general, the process had broken down the role of smoothing, so to be inserted to control the mesh grid income smoothing subdivision surface is better; when interpolating limit surface shape and its similarity in general interpolation surface smoothness are better. To be inserted as the design of the grid reflects the intent of the designer, and Catmul1. Clark subdivision is a subdivision approximation, limit surface shape and control the grid itself has some similarities, so this approach is conducive to the expression of the designer to shape. This treatment of the grid were inserted Doo. Sabin subdivision, the similarities are talking about here is the ultimate realization of the control grid interpolation M 'and the initial mesh M. Limit surface defined by the similarity between, as both have the same topology, in order to ensure efficiency,[link widoczny dla zalogowanych], the location of interpolation points and tangential similarities to the ultimate limit constraints to ensure that the surface smoothness, are based on similar to the smoothness constraints can be expressed for the next ... ・ nP = 0 (1) Ji + t ・ nPi. = 0 (2), under the''('/ Tp I a ('/ TpI). BU 0 (3) (1), equation (2) the interpolation point p \, equation (3) p ¨ tangent direction at the constraints, which (the I) I:. origin that position and tangent direction p perpendicular to the direction of a tangent. The above constraint is not normal constraint for the vertices, and for the law vertices are not added to the constraints of smoothness constraints. 3.4 perturbed optimization control mesh vertex interpolation constraints into account, method similar to the constraints, and smoothness-based constraints, in each iteration, assuming that part of the neighborhood vertex other than its limit points and the method to little effect, only the (. 『= 0,1, ..., m-1) to adjust, that is,[link widoczny dla zalogowanych], 8 = 0 (.『 = m,[link widoczny dla zalogowanych], m +1, ..., 4m a 1). To describe conveniently, remember =(:,:, ...,: a 。)=(:,:, ...,: a., o:, o:, ..., o: I a., b:, b:, ..., 6: I a., c:, c:, ..., c: I a.), namely: p \t is the coefficient matrix, introduced by the appropriate subdivision rules; vertex adjustment amount can be seen as the following optimization problem min: Σ '(4) Σ (+ = P? (5) .4 m ~ 1. (Σs State (+))= 0 (6), j = 0 '.4 m ~ 1. (t (+)) n: 0 (7) .4 m -. (s state (+)) ql'pI = 0 (8 ),, = 0 'where: a (') 'may be; type (2) is a
Adjustable multi-constrained Catmull-Clark Subdivision Surfaces
Limit point formula can be obtained '\may think that p \According to the above formula, consider adjusting the location of the interpolation methods to achieve peak due to P: \, ..., m-1) corresponding to the revised value of 8.1 Li '64m (m +5) p a (64m +273) Σ a Σ (23a ~ + +23 c ~)) If the target interpolation point P? and P \normal to n is' np; = 0, Ji p'np = 0 where: p \limit point; r ..., Ji ... are p \3.3 Based on similar smoothness constraint can be obtained despite the above constraints to meet the subdivision surface, but in many cases there will be not only smooth wrinkles and other phenomena, leading to limit surface quality is not high,[link widoczny dla zalogowanych], it is necessary to deal with smoothing If the constraint in achieving the interpolation after smoothing processing will not only affect the accuracy of interpolation and reduces the efficiency of the algorithm, so a better approach is to consider in the process of interpolation smoothing problem, that is the culmination of disturbance in the control process, In the geometric constraints and constraints smoothing the adjustment to optimize the amount of control points. [11] proposed the interpolation based on similarity proved to be an effective way to achieve smooth interpolation, in general, the process had broken down the role of smoothing, so to be inserted to control the mesh grid income smoothing subdivision surface is better; when interpolating limit surface shape and its similarity in general interpolation surface smoothness are better. To be inserted as the design of the grid reflects the intent of the designer, and Catmul1. Clark subdivision is a subdivision approximation, limit surface shape and control the grid itself has some similarities, so this approach is conducive to the expression of the designer to shape. This treatment of the grid were inserted Doo. Sabin subdivision, the similarities are talking about here is the ultimate realization of the control grid interpolation M 'and the initial mesh M. Limit surface defined by the similarity between, as both have the same topology, in order to ensure efficiency, the location of interpolation points and tangential similarity to the ultimate limit constraints to ensure smoothness of the surface, are based on similar to the smoothness constraints can be expressed for the next ... ・ nP = 0 (1) Ji + t ・ nPi. = 0 (2), under the''('/ Tp I a ('/ TpI). BU 0 (3) (1), equation (2) the interpolation point p \, equation (3) p ¨ tangent direction at the constraints, which (the I) I:. origin that position and tangent direction p perpendicular to the direction of a tangent. The above constraint is not normal constraint for the vertices, and for the law vertices are not added to the constraints of smoothness constraints. 3.4 perturbed optimization control mesh vertex interpolation constraints into account, method similar to the constraints, and smoothness-based constraints, in each iteration, assuming that part of the neighborhood vertex other than its limit points and the method to little effect, only the (. 『= 0,1, ..., m-1) to adjust, that is, 8 = 0 (.『 = m, m +1, ..., 4m a 1). To describe conveniently, remember =(:,:,[link widoczny dla zalogowanych], ...,: a 。)=(:,:, ...,: a., o:, o:, ..., o: I a., b:, b:, ..., 6: I a., c:, c:, ..., c: I a.), namely: p \t is the coefficient matrix, introduced by the appropriate subdivision rules; vertex adjustment amount can be seen as the following optimization problem min: Σ '(4) Σ (+ = P? (5) .4 m ~ 1. (Σs State (+))= 0 (6), j = 0 '.4 m ~ 1. (t (+)) n: 0 (7) .4 m -. (s state (+)) ql'pI = 0 (8 ),, = 0 'where: a (') 'may be; type (2) is a
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