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Min-Chi Ko

dblp:43/6072 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › skeletonization
medial axis transform
0.012000
Skeletonization of Three-Dimensional Object Using Generalized Potential Field · IEEE Trans. Pattern Anal. Mach. Intell. 2000
Geometric modeling and processing
skeletonization
0.012000
Skeletonization of Three-Dimensional Object Using Generalized Potential Field · IEEE Trans. Pattern Anal. Mach. Intell. 2000

Methods — techniques the papers use, named apart from their topics

newtonian potential · 0.0generalized potential function · 0.0
YearPublicationVenuePosition
2000 Skeletonization of Three-Dimensional Object Using Generalized Potential Field
abstract
In this paper, the potential-based skeletonization approach for 2D medial axis transform (MAT), which identifies object skeleton as potential valleys using a Newtonian potential model in place of the distance function, is generalized to three dimensions. The generalized potential functions given by Chung (1998), which decay faster with distance than the Newtonian potential, is used for the 3D case. The efficiency of the proposed approach results from the fact that these functions and their gradients can be obtained in closed forms for polyhedral surfaces. According to the simulation results, the skeletons obtained with the proposed approach are closely related to the corresponding MAT skeletons. While the medial axis (surface) is 2D in general for a 3D object, the potential valleys, being one-dimensional, form a more realistic skeleton. Other desirable attributes of the algorithm include stability against perturbations of the object boundary, the flexibility to obtain partial skeleton directly, and low time complexity.
Jen-Hui Chuang, Chi-Hao Tsai, Min-Chi Ko
IEEE Trans. Pattern Anal. Mach. Intell.3