We present new multilayer joint gait-pose manifolds (multilayer JGPMs) for complex human
gait motion modeling, where three latent variables are defined jointly in a low-dimensional …

As data-driven modeling becomes more prevalent for representing the uncertain dynamical
systems, concerns also arise regarding the reliability of these methods. Recent …

This paper develops a novel method for generating discrete equations of Lagrangian
mechanics that are constructed to evolve near subsets or submanifolds of the configuration …

充分利用形状蕴涵的语义信息进行三维形状的高层分析和理解是当前的热门话题.
提出采用形状部件的上下文语义关系进行功能识别的方法, 解决了当三维形状的几何特征和拓扑 …

Dramatic progress has been made in animating individual characters. However, we still lack
automatic control over activities between characters, especially those involving interactions …

A new method of spatial constraints-based maximum likelihood estimation (SC-based MLE)
is proposed to process latent variables data of incomplete human motions cycle, and …

In recent years, researchers have achieved great success in guaranteeing safety in human-
robot interaction, yielding a new generation of robots that can work with humans in close …

With the recent success of deep learning algorithms, many researchers have focused on
generative models for human motion animation. However, the research community lacks a …

This dissertation presents a series of fundamental approaches to the human motion analysis
from three perspectives, ie, manifold learning-based gait motion modeling, articulated shape …

This paper presents a two-layer gait representation framework for video-based human
motion estimation that extends our recent dual gait generative models, visual gait generative …