交互式地图转换:结合机器视觉和人工输入

F. Quek, Michael C. Petro
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引用次数: 2

摘要

在人机感知合作(HMPC)范式下,提出了一种将人类操作者的高级推理与机器感知相结合的交互式地图转换系统。HMPC定义了两种交互渠道:关注焦点(FOA),用户通过它引导机器感知的注意力,以及上下文。当用户通过指向设备在栅格地图上移动FOA时,智能光标会主动操作数据高亮显示对象以进行提取。FOA允许中央凹的重点,使用户能够改变电机精度与地图杂乱。HMPC在四个抽象层次上提供上下文。这允许系统的效率在数据质量恶化时优雅地降低。他们还提出了一种基于边界的线跟踪器,用于计算线的厚度,以及一种基于特征向量的孤立符号提取器。
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Interactive map conversion: combining machine vision and human input
The authors present an interactive map conversion system which combines a human operator's high level reasoning with machine perception under the Human-Machine Perceptual Cooperation (HMPC) paradigm. HMPC defines two channels of interaction: the focus of attention (FOA) by which the user directs the attention of machine perception, and context. As the user moves the FOA across a raster map display via a pointing device, a smart cursor operates proactively on the data highlighting objects for extraction. The FOA permits foveal emphasis, enabling the user to vary motor precision with map clutter. HMPC provides for contexts at four levels of abstraction. This permits the efficiency of the system to degrade gracefully as data quality worsens. They also present a boundary-based line follower which computes line thickness, and an isolated symbol extractor based on feature-vectors.<>
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