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Free-hand sketches for 3D model retrieval using cascaded LSDA

机译：使用级联LSDA进行3D模型检索的徒手草图

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摘要

This study proposes a novel cascaded 3D model retrieval framework for automatically and accurately fitting 3D models to user freehand 2D sketches (or object contours). The matching result provides the 3D geometry hypotheses of the 2D objects, and thus it is an important and fundamental part of several computer vision tasks, such as spatial layout estimation and scene understanding. However, existing matching approaches are still restricted by the corresponding point/line matching between the 2D image and the target 3D model. The limitation may make existing matching methods not online accessible in practice, and degrade their applicability. An alternative scenario is proposed to address this problem, in this paper. We use a retrieval system to collect a 3D-2D database offline, in which the 3D models are decomposed into 2D projected contours with respective to a limited number of different viewpoints. Our approach aims to enhance matching results by leveraging the extra database. Specifically, it optimizes a transformation from 3D objects to 2D contours, by which the target 3D object pose and categorization, to be recognized can be concisely estimated by entries in such database. More importantly, we demonstrate how to use a set of training images with limited pose variation to handle test images taken under uncontrolled view.
机译：这项研究提出了一种新颖的级联3D模型检索框架，用于自动准确地将3D模型拟合到用户徒手绘制的2D草图（或对象轮廓）。匹配结果提供了2D对象的3D几何假设，因此，它是一些计算机视觉任务（例如空间布局估计和场景理解）的重要组成部分。但是，现有的匹配方法仍然受到2D图像和目标3D模型之间的相应点/线匹配的限制。该限制可能会使现有的匹配方法在实践中无法在线访问，并降低其适用性。本文提出了一种替代方案来解决此问题。我们使用检索系统脱机收集3D-2D数据库，其中将3D模型分解为2D投影轮廓，并对应于有限数量的不同视点。我们的方法旨在通过利用额外的数据库来增强匹配结果。具体而言，它优化了从3D对象到2D轮廓的转换，通过该转换，可以通过此类数据库中的条目来简明地估计要识别的目标3D对象的姿势和分类。更重要的是，我们演示了如何使用姿势变化有限的一组训练图像来处理在不受控制的视图下拍摄的测试图像。

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