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时间:2008-08-21 作者: 点击数:

22日下午16:00和23日上午9:00在逸夫楼1107报告厅,香港大学王文平教授将作两场学术报告,请各位老师和同学们届时参加,以下是两场报告的相关内容:

Talk 1

Title: Fast and Stable Optimization for Curve and Surface Fitting

Professor Wenping Wang

Department of Computer Science

TheUniversityofHong Kong

Abstract:

We present the squared distance minimization (SDM) method for fitting

a B-spline curve to a model shape defined by unorganized and noisy

data points. We introduce a new fitting error term, called the squared

distance (SD) error term, defined by a quadratic approximation of

squared distances from data points to a fitting curve. Through

iterative minimization of the SD error term, SDM makes a properly

specified initial B-spline curve converge towards the model shape.

Because the SD error term measures faithfully the geometric distance

between a fitting curve and a model shape, SDM attains faster and more

stable convergence than commonly used previous methods. To explain the

superior performance of SDM, we show that SDM can be interpreted as a

Newton-like method which employs an adaptively simplified

approximation to the Hessian of the objective function. The extension

of the SDM method to surface fitting will be discussed.

Talk 2

Title: Intersection and collision detection for Quadrics Surfaces

Professor Wenping Wang

Department of Computer Science

TheUniversityofHong Kong

Abstract:

We give complete classification of morphologies of the intersection

curves of two quadrics (QSIC) in 3D real projective space. For each of

QSIC morphologies we establish a characterizing algebraic condition

expressed in terms of the number of real roots of the characteristic

equation of two quadric surfaces, the multiplicities of these roots,

and the signature of the pencil between and at these roots, with all

this information encoded in an index sequence and the Segre

characteristics. The key technique used for deriving these conditions

is analyzing two simple quadrics in canonical forms of a pair of

quadrics under simultaneous congruence. In the special cases of

ellipsoids, we apply these results to develop new methods for

efficient continuous collision detection of moving ellipsoids.

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