In this paper, we study a new method in shape adjustment ofS-λcurves. By examples of finite and infinite degree generation function, we get the conclusion thatS-λcurves can be adjusted by perturbation of generation functionS（t）while the control points and parameters hold.
We present the best bounds on the distance between 3-direction quartic box spline surface patch and its control net by means of analysis and computing for the basis functions of 3-direction quartic box spline surface.Both the local bounds and the global bounds are given by the maximum norm of the first differences or second differences or mixed differences of the control points of the surface patch.
In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspaee approach to classify the test sample. In order to adapt all the eases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low ~ample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.
We introduce a kind of shape-adjustable spline curves defined over a non-uniform knot sequence.These curves not only have the many valued properties of the usual non-uniform B-spline curves,but also are shape adjustable under fixed control polygons.Our method is based on the degree elevation of B-spline curves,where maximum degrees of freedom are added to a curve parameterized in terms of a non-uniform B-spline.We also discuss the geometric effect of the adjustment of shape parameters and propose practical shape modification algorithms,which are indispensable from the user's perspective.
