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VISUAL INFORMATION FOR REACH AND GRASP

便于获取和掌握的视觉信息

基本信息

批准号：
2888522
负责人：
DANIEL J KERSTEN
金额：
$ 9.86万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
1996
资助国家：
美国
起止时间：
1996-07-01 至 2001-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/2888522
关键词：
arm behavioral /social science research tag body movement cues hand human subject neural information processing size perception visual depth perception visual feedback visual perception visual stimulus

项目摘要

DESCRIPTION: Knowledge of how visual information determines perceived depth and shape has grown considerably in the past few decades. We know less, however, about how this knowledge relates to performance in everyday tasks. It is widely appreciated that perceived depth is important for determining large scale spatial layout for a variety of actions, and that shape perception is important for object recognition. However, the visual information for depth and shape also provides critical image measurements for programming reach and grasp by the hand. Despite the importance of vision for prehension, we know surprisingly little about how multiple sources of visual information are used for hand movements. A central issue is the degree to which perceptual judgements of shape and depth predict measures of reaching and grasping. A common working hypothesis is that motor planning makes use of the full perceptual "reconstruction" of the scene to program its movements. The investigator will critically examine this assumption in a series of experiments. In particular, he plans to 1) compare visual processing for reaching with that for conscious perceptual judgements of depth under cue conflict situations; 2) understand how multiple cues for depth, size, and orientation combine to determine reach and grasp; 3) examine the role of dependence on learned views of an object for grasping. These studies will make use of recently acquired laboratory instrumentation which allows computer-controlled presentation of both real and synthetic visual stimuli together with real-time monitoring of movements.

描述：了解视觉信息如何决定感知深度在过去的几十年里，形状有了很大的发展。我们知道的更少，然而，关于这些知识如何与日常任务的表现有关。广泛认识到，感知深度对于确定大规模空间布局，各种行动，和形状感知对于物体识别是重要的。然而，视觉上深度和形状的信息也提供了关键的图像测量用于编程手的触及和抓握。尽管重要的是我们对多媒体技术的发展，视觉信息源用于手部运动。一个中心问题是形状和深度的知觉判断预测的程度达到和把握的措施。一个常见的工作假设是，运动规划利用了对运动的完全知觉“重建”，场景来编程它的动作。调查人员将严格审查在一系列实验中证明了这一假设。特别是，他计划1）比较视觉处理的达到与有意识的知觉线索冲突情境下的深度判断; 2）理解如何深度、大小和方向的多个线索结合联合收割机来确定范围 3）考察依赖对习得的客体观的作用抓东西这些研究将利用最近获得的实验室仪器，允许计算机控制的表现，真实的和合成视觉刺激，以及实时监测动作