Similarities in Object and Event Segmentation: A Geometric Approach to Event Path Segmentation

Abstract

Events, like objects, can be decomposed into parts. Path, the spatiotemporal trajectory of an object during an event, is the most commonly labeled event feature across the world's languages, provides important social information, and is increasingly central to theories of general event segmentation. However, little is understood about how adults visually segment paths. We apply theories developed for object segmentation to help understand path segmentation. Overall subjects segmented equivalent object shapes and event paths in similar ways following patterns predicted by Singh and Hoffman's (2001) Singh, M. and Hoffman, D. D. 2001. “Parts-based representations of visual shape and implications for visual cognition.”. In From fragments to objects—Segmentation and grouping in vision Edited by: Shipley, T. F. and Kellman, P. J. 401–459. New York, NY: Elsevier Science..  [Google Scholar] geometric analysis of object parts. There were two notable differences between object and event segmentation: (1) event parsing occurred at points of negative curvature minima and positive curvature maxima as opposed to simply negative curvature minima; and (2) event parsing was more frequent and variable than object parsing. Implications of these results for event perception and categorization are discussed.     

一种基于标识的增强现实交互方法

增强现实系统中,不同标识上虚拟物体交互行为比较单一,且大多根据标识问的距离控制交互,当系统中标识增多时,系统的运行效率将大大降低。本文将虚拟现实中的感知技术引入到系统中,为虚拟物体建立了一种基于空间距离的感知模型,将标识间的距离分级,虚拟物体对处于自己感知域内不同距离级别上的其它虚拟物体采取不同的交互行为。实验结果表明,该方法可以丰富虚拟物体的交互行为,同时满足系统实时性需求。     

Evidence for Amodal Representations after Bimodal Learning: Integration of Haptic-Visual Layouts into a Common Spatial Image

Abstract

Participants learned circular layouts of six objects presented haptically or visually, then indicated the direction from a start target to an end target of the same or different modality (intramodal versus intermodal). When objects from the two modalities were learned separately, superior performance for intramodal trials indicated a cost of switching between modalities. When a bimodal layout intermixing modalities was learned, intra- and intermodal trials did not differ reliably. These findings indicate that a spatial image, independent of input modality, can be formed when inputs are spatially and temporally congruent, but not when modalities are temporally segregated in learning.     

Monitoring Object Orientation: Effects of Layout Complexity,Viewpoint Changes,and Object Function

Spatial short-term memory for single target positions is subject to distortions which depend on the spatial layout of visual landmarks. Here, participants had to reproduce the positions of briefly presented targets in the context of three-landmark configurations presented in various orientations. Symmetry properties of distortional patterns were determined by the intrinsic reference system of the landmark configuration as well as by the environment-or body-centered vertical axis. Symmetry was best about the cardinal axes of the landmark system irrespective of their orientation, but symmetry of non-cardinal axes was enhanced when these axes were aligned with the extrinsic vertical. Results are inconsistent with most current models of spatial memory distortions but in line with models explaining distortions in terms of attentional processes in topographical neuronal networks.     

智能移动机器人导航控制技术综述

智能移动机器人在制造业、服务业、军事、星际探测等领域获得了广泛的应用,导航是智能移动机器人实现自主控制需要解决的重要问题.对不同领域智能移动机器人导航技术发展现状进行了调研.针对环境感知与建模、定位和路径规划等机器人导航控制关键技术,深入分析了其实现方法.在此基础上归纳出智能移动机器人导航控制未来的发展趋势.     

无人飞行器三维类脑SLAM自主导航方法

随着动物大脑中导航细胞的发现以及人工智能的快速发展,受动物启发的类脑SLAM自主导航方法为突破现有导航方式的瓶颈提供了新的思路。本文针对无人飞行器类脑SLAM自主导航技术的研究进展进行了综述, 包括：1）论述无人飞行器SLAM技术研究现状;2）在二维SLAM导航技术的基础上介绍了三维空间以及单一环境下的类脑SLAM自主导航方案;3）分析了二维及三维类脑SLAM自主导航方案的关键技术;4）最后对现有三维导航方案进行分析验证并指出目前类脑SLAM在无人飞行器上应用时亟需解决的问题。类脑SLAM技术不依赖于高精度传感器、对环境适应性强、自主智能性高,更加适用于无人飞行器复杂动态的飞行环境。     

非合作目标智能感知技术研究进展与展望

智能感知是实现航天器在轨精细化操控过程的关键技术,是在轨服务技术智能化的重点发展方向之一。空间目标智能感知包括位姿测量、三维重建与部位识别等关键技术,涉及小样本、多模态、模型适应与高维数据等问题。从工程应用角度出发,对非合作目标智能感知技术的研究现状进行系统的梳理与总结。首先,总结典型非合作在轨感知系统与光学敏感器技术的发展现状;其次,归纳总结了非合作目标智能感知涉及的关键技术;最后,基于研究现状总结和关键技术分析,探讨了非合作目标智能感知目前存在的主要问题,并给出后续发展的建议。     

空间立体信息缺失对机械臂遥操作任务的影响

视觉作为人认知环境的主要信息通道,在空间遥操作任务中有极其重要的作用。本研究面向空间站机械臂遥操作任务,通过对24名被试进行机械臂遥操作模拟平台实验,探索不同程度空间立体信息缺失对机械臂遥操作绩效、脑力负荷、距离感知和情境意识的影响,剖析不同立体信息在遥操作过程中的作用。实验结果表明:局部立体信息对提高遥操作任务完成率、减少撞击操作等指标有重要作用;而全局立体信息更有利于减少机械臂冗余行走距离和限位操作次数;两者对脑力负荷水平的降低有显著影响,而对距离估计偏差和情境意识水平影响不显著。因此,根据不同任务类型选取合适的立体信息补偿,从多个角度完善立体信息的呈现对于保障遥操作任务的顺利进行具有重要意义。     

触觉信息表征技术与分类感知试验

面向空间智能精细化操作的需求,采用提取触觉传感信息的方式对目标进行识别。在动态序列匹配(dynamic time warping,DTW)距离的基础上,应用DTW核实现对触觉序列信息的高效表征,提出了触觉序列的联合稀疏编码算法,用于一个单独时间序列的不同手指间触觉信息的简单融合。对训练样本进行学习构建数据库,用不同的触觉反馈信息进行典型目标的分类试验,总体识别率为90.07%。触觉联合稀疏编码算法不仅简单而且能挖掘不同手指采集的触觉信息指尖的内在联系,为操控目标的智能化识别提供一种有效的途径,未来可用于在轨服务。