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Simulating Fixations When Looking at Visual Arts

机译:看视觉艺术时模拟注视

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摘要

When people look at pictures, they fixate on specific areas. The sequences of such fixations are so characteristic for certain pictures that metrics can be derived that allow successful grouping of similar pieces of visual art. However, determining enough fixation sequences by eye tracking is not practically feasible for large groups of people and pictures. In order to get around this limitation, we present a novel algorithm that simulates eye movements by calculating scan paths for images and time frames in real time. The basis of our algorithm is an attention model that combines and optimizes rectangle features with Adaboost. The model is adapted to the characteristics of the retina, and its input is dependent on a few earlier fixations. This method results in significant improvements compared to previous approaches. Our simulation process delivers the same data structures as an eye tracker, thus can be analyzed by standard eye-tracking software. A comparison with recorded data from eye tracking experiments shows that our algorithm for simulating fixations has a very good prediction quality for the stimulus areas on which many subjects focus. We also compare the results with those from earlier works. Finally, we demonstrate how the presented algorithm can be used to calculate the similarity of pictures in terms of human perception.
机译:人们查看图片时,会专注于特定区域。这种固定的序列对于某些图片来说是如此具有特征性,以致于可以得出度量标准,从而可以成功地将相似的视觉艺术作品分组。然而,对于大群人和图片,通过眼睛跟踪确定足够的注视顺序实际上是不可行的。为了解决此限制,我们提出了一种新颖的算法,该算法通过实时计算图像和时间范围的扫描路径来模拟眼睛的运动。我们算法的基础是一个注意力模型,该模型结合并优化了Adaboost的矩形特征。该模型适合于视网膜的特征,其输入取决于一些较早的注视。与以前的方法相比,此方法带来了显着的改进。我们的仿真过程提供与眼动仪相同的数据结构,因此可以通过标准的眼动仪软件进行分析。与来自眼睛跟踪实验的记录数据进行的比较表明,我们的模拟注视算法对许多对象关注的刺激区域具有很好的预测质量。我们还将结果与早期作品的结果进行比较。最后,我们演示了如何将本文提出的算法用于根据人的感知来计算图片的相似度。

著录项

  • 来源
    《ACM Transactions on Applied Perception (TAP)》 |2015年第3期|9.1-9.20|共20页
  • 作者单位

    Institute for Visualization and Interactive Systems (VIS), University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany;

    Institute for Visualization and Interactive Systems (VIS), University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany;

    Institute for Visualization and Interactive Systems (VIS), University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany;

    Institute for Visualization and Interactive Systems (VIS), University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Visual attention; eye movement; perception;

    机译:视觉注意力;眼动知觉;
  • 入库时间 2022-08-17 23:18:14

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