论文标题
将打印设计文件与产品照片匹配的混合框架
A Hybrid Framework for Matching Printing Design Files to Product Photos
论文作者
论文摘要
我们提出了一个实时图像匹配框架，它是使用手工制作的功能和从经过良好调整的深度卷积网络获得的深度功能的意义上的混合动力。我们专注于某个应用程序的匹配问题，即针对产品照片匹配的打印设计。打印设计是使用设计工具创建的任何类型的模板图像文件，因此是完美的图像信号。但是，印刷产品的照片具有许多不必要的效果，例如不受控制的射击角，不受控制的照明，遮挡，颜色的印刷缺陷，相机噪音，光学模糊等。为此，我们创建了一个图像集，其中包括打印设计和相应的产品照片对，并与实际打印设施的协作。使用此图像集，我们基准了各种手工制作和深度功能，以匹配性能，并提出了一个框架，其中深度学习的用途最高，但没有使用普通的台式计算机禁用实时操作。
We propose a real-time image matching framework, which is hybrid in the sense that it uses both hand-crafted features and deep features obtained from a well-tuned deep convolutional network. The matching problem, which we concentrate on, is specific to a certain application, that is, printing design to product photo matching. Printing designs are any kind of template image files, created using a design tool, thus are perfect image signals. However, photographs of a printed product suffer many unwanted effects, such as uncontrolled shooting angle, uncontrolled illumination, occlusions, printing deficiencies in color, camera noise, optic blur, et cetera. For this purpose, we create an image set that includes printing design and corresponding product photo pairs with collaboration of an actual printing facility. Using this image set, we benchmark various hand-crafted and deep features for matching performance and propose a framework in which deep learning is utilized with highest contribution, but without disabling real-time operation using an ordinary desktop computer.
