Joint estimation of the human body is suitable for many fields such as human–computer
interaction, autonomous driving, video analysis and virtual reality. Although many depth …

We propose a viewpoint invariant model for 3D human pose estimation from a single depth
image. To achieve this, our discriminative model embeds local regions into a learned …

We propose to combine recent Convolutional Neural Networks (CNN) models with depth
imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to …

In the problem of domain transfer learning, we learn a model for the prediction in a target
domain from the data of both some source domains and the target domain, where the target …

Robust human pose estimation and tracking plays an integral role in assistive service robot
applications, as it provides information regarding the body pose and motion of the user in a …

Human pose estimation is considered one of the major challenges in the field of Computer
Vision, playing an integral role in a large variety of technology domains. While, in the last …

We present CrossInfoMobileNet, a hand pose estimation convolutional neural network
based on CrossInfoNet, specifically tuned to mobile phone processors through the …

Pose tracking from range image sequences remains a difficult task due to strong noise and
serious self-occlusion of human body. Existing work either rely on extremely large and …

Featured Application This study proposes an upper extremity rehabilitation system using
efficient action identification system for home based on color and depth sensor information …

摘要高斯过程回归(Gaussian process regression, GPR) 是一种广泛应用的回归方法,
可以用于解决输入输出均为多元变量的人体姿态估计问题. 计算复杂度是高斯过程回归的一个 …