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Human perception of trademark images: implications for retrieval system design

机译：人类对商标图像的感知：对检索系统设计的影响

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Abstract: Modeling human shape similarity judgments involves identifying perceptually significant image elements, selecting appropriate features to represent their shape, and computing suitable similarity measures. This paper is concerned with the first of these - identification of the way in which humans segment abstract trademark images. A sample of 63 trademark images was shown to several groups of students from different subject backgrounds in two experiments. Students were first presented with printed versions of a number of abstract trademark images, and invited to sketch their preferred segmentation of each image. A second group of studies was then shown each image, plus its set of alternative segmentations, and invited to rank each alternative in order of preference. The degree of agreement over how images should be segmented varied substantially form one image to another. Qualitative analysis of our result suggested that participants used a relatively small number of segmentation strategies, reflecting well-known psychological principles. Agreement between human image segmentations and those generated by our ARTISAN trademark retrieval system was quite limited, indicating that ARTISAN is currently capable of modeling only a small subset of the mechanisms used by human participants. The implications of these experiments for the future development of ARTISAN are discussed. !35
机译：摘要：对人体形状相似性判断进行建模涉及到识别可感知的重要图像元素，选择合适的特征来表示其形状，以及计算合适的相似性度量。本文关注的是第一个问题-识别人类分割抽象商标图像的方式。在两个实验中，向来自不同学科背景的几组学生展示了63张商标图像的样本。首先向学生展示了许多抽象商标图像的印刷版本，然后邀请他们为每个图像绘制他们喜欢的分割图。然后，向第二组研究显示每个图像及其替代分割集，并邀请他们按偏好顺序对每个替代进行排序。关于如何分割图像的一致性程度从一个图像到另一个图像基本上是变化的。对我们结果的定性分析表明，参与者使用了相对较少的细分策略，反映了众所周知的心理原理。人类图像分割与我们的ARTISAN商标检索系统生成的图像分割之间的协议非常有限，这表明ARTISAN目前仅能够对人类参与者使用的机制的一小部分进行建模。讨论了这些实验对ARTISAN未来发展的意义。 ！35

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