• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国政府科技报告 >Computational Model of Active Vision for Visual Search in Human- Computer Interaction
【24h】

Computational Model of Active Vision for Visual Search in Human- Computer Interaction

机译：人机交互中视觉搜索主动视觉的计算模型

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Human visual search plays an important role in many human-computer interaction (HCI) tasks. Better models of visual search are needed not just to predict overall performance outcomes, such as whether people will be able to find the information needed to complete an HCI task, but to understand the many human processes that interact in visual search, which will in turn inform the detailed design of better user interfaces. This article describes a detailed instantiation, in the form of a computational cognitive model, of a comprehensive theory of human visual processing known as 'active vision' (Findlay & Gilchrist, 2003). The computational model is built using the EPIC (Executive Process-Interactive Control) cognitive architecture. Eye tracking data from three experiments inform the development and validation of the model. The modeling asks--and at least partially answers--the four questions of active vision: (1) What can be perceived in a fixation; (2) When do the eyes move; (3) Where do the eyes move; (4) What information is integrated between eye movements. Answers include: (1) Items nearer the point of gaze are more likely to be perceived, and the visual features of objects are sometimes misidentified. (2) The eyes move after the fixated visual stimulus has been processed (i.e., has entered working memory). (3) The eyes tend to go to nearby objects. (4) Only the coarse spatial information of what has been fixated is likely maintained between fixations. The model developed to answer these questions has both scientific and practical value in that the model gives HCI researchers and practitioners a better understanding of how people visually interact with computers, and provides a theoretical foundation for predictive analysis tools that can predict aspects of that interaction.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号