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.