Myungsoo Bae

A hybrid approach to feature segmentation of triangle meshes

Abstract Segmentation of a polygonal mesh is a method of breaking the mesh down into ‘meaningful’ connected subsets of meshes called regions or features. Several methods have been proposed in the past and they are either vertex based or edge based. The vertex method used here is based on the watershed segmentation scheme which appears prominently in the image segmentation literature and was later applied to the 3D segmentation problem [9] , [10] . Its main drawback is that it is a vertex based method and no hard boundaries (edges) are created for the features or regions. Edge based methods rely on the dihedral angle between polygon faces to determine if the common edge should be classified as a Feature Edge. However, this method results in many disconnected edges and thereby incomplete feature loops. We propose a hybrid method which takes advantage of both methods mentioned earlier and create regions with complete feature loops. Satisfactory results have been achieved for both CAD parts as well as other laser scanned objects such as bones and ceramic vessels.

Curvature estimation scheme for triangle meshes using biquadratic Bézier patches

When dealing with triangle meshes, it is often important to compute curvature information for the purposes of feature recognition, segmentation, or shape analysis. Since a triangle mesh is a piecewise linear surface, curvature has to be estimated. Several different schemes have been proposed, both discrete and continuous, i.e. based on fitting surfaces locally. This paper compares commonly used discrete and continuous curvature estimation schemes. We also present a novel method which uses biquadratic Bezier patches as a local surface fitting technique.

Automated 3D Face authentication & recognition

This paper presents a fully automated 3D face authentication (verification) and recognition (identification) method and recent results from our work in this area. The major contributions of our paper are: (a) the method can handle data with different facial expressions including hair, upper body, clothing, etc. and (b) development of weighted features for discrimination. The input to our system is a triangular mesh and it outputs a matching % against a gallery. Our method includes both surface and curve based features that are automatically extracted from a given face data. The test set for authentication consisted of 117 different people with 421 scans including different facial expressions. Our study shows equal error rate (EER) at 0.065% for normal faces and 1.13% in faces with expressions. We report verification rates of 100% in normal faces and 93.12% in faces with expressions at 0.1% FAR. For identification, our experiment shows 100% rate in normal faces and 95.6% in faces with expressions. From our experiment we conclude that combining feature points, profile curve, and partial face surface matching gives better authentication and recognition rate than any single matching method.

Shape modeling for 3D archaeological vessels

This chapter presents a method for archiving and searching three-dimensional Native American ceramic vessels using geometric modeling techniques. Archaeological vessels are scanned and defined as a set of 3D triangulated meshes composed of points, edges and triangles. Our work includes modeling the data with parametric surfaces, extracting features to raise the level of abstraction of data, and organizing vessel data based on XML schema. A visual query interface on the web was developed that permits users to sketch or select sample vessel shapes to augment text and metric search criteria to retrieve original and modeled data, and interactive 2D and 3D models.