Large Image Collections - Comprehension and Familiarization by Interactive Visual Analysis
Large Image Collections - Comprehension and Familiarization by Interactive Visual Analysis
复制标题
大型图像集 - 通过交互式视觉分析理解和熟悉
DOI：
10.1007/978-3-642-02115-2_2
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发表时间：
2009
影响因子：
19.5
通讯作者：
H. Hauser
中科院分区：
文献类型：
--
作者：
K. Matkovič;D. Gračanin;W. Freiler;Jana Banova;H. Hauser
图像集合的大尺寸和复杂的多维特征需要多方面的探索和分析方法，以提供更好的理解和欣赏。我们探索由图像和描述图像的参数组成的大型且复杂的数据集。我们描述了一种新颖的方法，为探索和理解此类数据集提供了新的、令人兴奋的机会。我们利用协调的多个视图对所有参数进行交互式视觉分析。除了图像参数空间中的迭代细化和深入研究之外，探索此类数据集还需要不同的方法，因为视觉内容无法完全参数化。我们同时刷视觉内容和图像参数值。用户除了提供完整的图像参数规范之外，还提供刷牙的视觉提示（使用图像）。我们在来自 Flickr 的超过 26,000 张图像的数据集上说明了我们的方法。所开发的方法可用于许多应用领域，包括社会学、营销或日常使用。
Large size and complex multi-dimensional characteristics of image collections demand a multifaceted approach to exploration and analysis providing better comprehension and appreciation. We explore large and complex data-sets composed of images and parameters describing the images. We describe a novel approach providing new and exciting opportunities for the exploration and understanding of such data-sets. We utilize coordinated, multiple views for interactive visual analysis of all parameters. Besides iterative refinement and drill-down in the image parameters space, exploring such data-sets requires a different approach since visual content cannot be completely parameterized. We simultaneously brush the visual content and the image parameter values. The user provides a visual hint (using an image) for brushing in addition to providing a complete image parameters specification. We illustrate our approach on a data-set of more than 26,000 images from Flickr . The developed approach can be used in many application areas, including sociology, marketing, or everyday use.