Tagging-by-search: automatic image region labeling using gaze information obtained from image search

T. Walber, Chantal Neuhaus, A. Scherp
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引用次数: 1

Abstract

Labeled image regions provide very valuable information that can be used in different settings such as image search. The manual creation of region labels is a tedious task. Fully automatic approaches lack understanding the image content sufficiently due to the huge variety of depicted objects. Our approach benefits from the expected spread of eye tracking hardware and uses gaze information obtained from users performing image search tasks to automatically label image regions. This allows to exploit the human capabilities regarding the visual perception of image content while performing daily routine tasks. In an experiment with 23 participants, we show that it is possible to assign search terms to photo regions by means of gaze analysis with an average precision of 0.56 and an average F-measure of 0.38 over 361 photos. The participants performed different search tasks while their gaze was recorded. The results of the experiment show that the gaze-based approach performs significantly better than a baseline approach based on saliency maps.
搜索标记:利用从图像搜索中获得的凝视信息自动标记图像区域
标记的图像区域提供了非常有价值的信息,可以用于不同的设置,如图像搜索。手工创建区域标签是一项繁琐的任务。由于所描绘的对象种类繁多,全自动方法缺乏对图像内容的充分理解。我们的方法受益于眼动追踪硬件的预期普及,并使用从执行图像搜索任务的用户获得的凝视信息来自动标记图像区域。这允许在执行日常任务时利用人类对图像内容的视觉感知能力。在一项有23名参与者的实验中,我们证明了通过凝视分析来为照片区域分配搜索词是可能的,平均精度为0.56,平均f值为0.38。参与者在进行不同的搜索任务时,他们的目光会被记录下来。实验结果表明,基于注视的方法明显优于基于显著性图的基线方法。
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