arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1903.04448cs.OHcs.AI
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语用推理和视觉抽象使视觉交际中的语境灵活性成为可能

Pragmatic inference and visual abstraction enable contextual flexibility during visual communication

Stanford University(斯坦福大学);University of California, San Diego(加利福尼亚大学圣迭戈分校)

Judith Fan, Robert Hawkins, Mike Wu, Noah Goodman

摘要:

视觉交流方式在现代生活中无处不在-从地图到数据图再到政治漫画。在这里,我们研究绘画,视觉传达的最基本形式。参与者在一个在线环境中配对,玩一个基于绘画的参考游戏。在每次试验中,两名参与者都被展示了相同的四个物体,但位置不同。草图绘制者的目标是绘制这些对象之一,以便查看者可以从数组中选择它。在“近距离”试验中,物体属于同一基本级别类别,而在“远距离”试验中,物体属于不同类别。我们发现,人们利用共享的信息来有效地交流目标对象:在远距离试验中,素描者在使用更少的笔画,使用更少的墨水和花费更少的时间在他们的绘画上的同时实现了高识别准确率。我们假设,人类成功地完成这项任务是通过招募两个核心能力:视觉抽象,感知物体与其绘画之间的对应关系的能力;以及语用推理,判断哪些信息可以帮助观众区分目标和干扰物的能力。为了评估这一假设,我们开发了一个包含这两种能力的素描器计算模型,实例化为嵌套在概率程序中的深度卷积神经网络。我们发现这个模型很好地拟合了人类数据,并且优于病变变体。总之,这项工作提供了视觉感知和社会认知如何共同支持视觉传达中的上下文灵活性的第一个算法明确的理论。

英文摘要:

Visual modes of communication are ubiquitous in modern life --- from maps to data plots to political cartoons. Here we investigate drawing, the most basic form of visual communication. Participants were paired in an online environment to play a drawing-based reference game. On each trial, both participants were shown the same four objects, but in different locations. The sketcher's goal was to draw one of these objects so that the viewer could select it from the array. On `close' trials, objects belonged to the same basic-level category, whereas on `far' trials objects belonged to different categories. We found that people exploited shared information to efficiently communicate about the target object: on far trials, sketchers achieved high recognition accuracy while applying fewer strokes, using less ink, and spending less time on their drawings than on close trials. We hypothesized that humans succeed in this task by recruiting two core faculties: visual abstraction, the ability to perceive the correspondence between an object and a drawing of it; and pragmatic inference, the ability to judge what information would help a viewer distinguish the target from distractors. To evaluate this hypothesis, we developed a computational model of the sketcher that embodied both faculties, instantiated as a deep convolutional neural network nested within a probabilistic program. We found that this model fit human data well and outperformed lesioned variants. Together, this work provides the first algorithmically explicit theory of how visual perception and social cognition jointly support contextual flexibility in visual communication.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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