Yonghuai Liu

TL;DR: This study serves to give a comprehensive survey of both types of registration, focusing on three-dimensional point clouds and meshes, and shows how overfitting arises in nonrigid registration and the reasons for increasing interest in intrinsic techniques.

TL;DR: This paper proposes a novel practical algorithm that directly manipulates the possible point matches established by the traditional ICP criterion based on both the collinearity and closeness constraints without any feature extraction, image pre-processing, or motion estimation from outliers corrupted data.

TL;DR: This research aims to address non-predictive or inaccurate weather forecasting by developing and evaluating a lightweight and novel weather forecasting system, which consists of one or more local weather stations and state-of-the-art machine learning techniques for weather forecasting using time-series data from these weather stations.

TL;DR: The benefits of the proposed method are further evaluated in applications such as mesh simplification, mesh segmentation, and scan integration, where it is shown how incorporating mesh saliency can provide improved results.

TL;DR: The results show that the level of agreement varies significantly between the users for the selection of key frames, which denotes the hidden challenge in automatic video summary evaluation.