Robust Mesh Segmentation Using Feature-Aware Region Fusion

Abstract

This paper introduces a simple but powerful segmentation algorithm for 3D meshes. Our algorithm consists of two stages: over-segmentation and region fusion. In the first stage, adaptive space partition is applied to perform over-segmentation, which is very efficient. In the second stage, we define a new intra-region difference, inter-region difference, and fusion condition with the help of various shape features and propose an iterative region fusion method. As the region fusion process is feature aware, our algorithm can deal with complex 3D meshes robustly. Massive qualitative and quantitative experiments also validate the advantages of the proposed algorithm.

Automation of Language Sample Analysis

“…Fortunately, the TalkBank corpora already contain many Gold Standard utterances that were segmented by hand in accordance with the required standards. Using these data, we trained a novel utterance segmentation model consistent with the existing literature ( Wu et al, 2022 ) that treats text segmentation as a token-level sequence labeling punctuation restoration task.…”