Qinping Zhao

In virtual reality (VR) applications, hand-controller interaction is largely limited by the biomechanical structure of the arm and its kinematical features. Earlier research revealed that different arm postures generate distinct arm fatigue levels in mid-air operational tasks; however, how they impact interaction performance, e.g., accuracy of target grasp and manipulation, has been less investigated. To fill this gap in knowledge, we conducted an empirical experiment in which thirty participants were recruited to complete a series of target acquisition tasks in a specifically designed VR application. Results show that (1) a bent arm posture resulted in a higher interaction accuracy than a stretched arm posture; (2) a downward arm posture interacted more accurately than an upraised arm posture; since two arms are bilaterally symmetric, (3) either selected arm interacted more accurately on the corresponding side than on the opposite side; and (4) the user-preferred or dominant arm interacted more persistently than the non-dominant one, though two arms generated little difference in interaction accuracy. Implications and suggestions are discussed for designing more efficient and user-satisfying interactive spaces in VR.

“健康中国”国家战略对高质量医学教育、高水平手术研究、精准临床诊疗提出了新的要求。面向国家新医科战略发展布局，本文在概述虚拟现实概念、核心价值及其对行业支撑作用的基础上，对虚拟现实技术在新医科人才培养中的作用进行了探讨，并以典型案例的形式，详细剖析了虚拟现实技术在口腔医学和临床医学相关的实操教学、技能考核、在线自主训练、临床思维实训等方面所发挥的重要作用，以期为新医科人才培养的模式创新提供有益经验借鉴。

Pedestrian detection and human pose estimation are instructive for reconstructing a three-dimensional scenario and for robot navigation, particularly when large amounts of vision data are captured using various data-recording techniques. Using an unrestricted capture scheme, which produces occlusions or breezing, the information describing each part of a human body and the relationship between each part or even different pedestrians must be present in a still image. Using this framework, a multi-layered, spatial, virtual, human pose reconstruction framework is presented in this study to recover any deficient information in planar images. In this framework, a hierarchical parts-based deep model is used to detect body parts by using the available restricted information in a still image and is then combined with spatial Markov random fields to re-estimate the accurate joint positions in the deep network. Then, the planar estimation results are mapped onto a virtual three-dimensional space using multiple constraints to recover any deficient spatial information. The proposed approach can be viewed as a general pre-processing method to guide the generation of continuous, three-dimensional motion data. The experiment results of this study are used to describe the effectiveness and usability of the proposed approach.

Clouds are important components of the fascinating natural images. However, extracting cloud shapes from images remains a challenging task. This paper presents a calculation method for estimating the shape of a cumulus cloud from a single image suitable for flight simulations and games. The shape of the cloud is assumed to be symmetric. Based on this assumption, the intensities of pixels are correlated with the geometry of a cloud's surface via a simplified single scattering model. A propagation scheme is designed to derive the surface progressively, and mesh editing techniques are used to improve the surface. Finally, the cloud is represented by a particle system. The results show that the proposed method can generate realistic cumulus clouds that are similar to those found in the images in terms of the shape distribution.

Texture atlas is widely used in many applications such as texture mapping, 3D Paint and illumination map texture synthesis etc. Several methods have been proposed for generating texture atlas, but most of them are not compact enough for some applications or require too much manual intervention. This paper presents a fully automatic BFD approach to generate compact texture atlas for triangular mesh models. Our main contribution is making some modifications to a piecewise mesh parameterization method to control the shape of charts by introducing a new local criterion, and developing a novel rectangle-packing algorithm.

It is important to design an agent with logical and decisive rationality in agent organization. Study about organization focuses on the definition of agent organization model and the analysis of organization formation and evolution, an attractive and challenging issue is how to combine logical and decisive rationality into a uniform framework. This paper aims at arguing the combination with logic and decision in agent organization. To pursue this aim, we extend the notions of commitment and obligation with utility in agent organization and utility reflects agent decision. In order to systematize the notions, formal tools are introduced to describe them as well as the semantics of utility for commitment and obligation are defined. We specify the properties and consequences of the extension for agent organization