KDI: 3D Free-Form Models for Geometric Recovery and Applications to Archaeology

在国家科学基金会的支持下，David Cooper博士和他的同事将开发一种技术，用于从一张或多张图像和视频中恢复3D自由形状物体和选定场景结构。该技术基于3D形状表示和半交互式混合主动系统的发展，以及机器决策导向的贝叶斯表面估计。这项工作的主要重点是开发用于考古遗址和人工制品重建和建筑的工具。这将影响低水平的形状模型，以及如何将它们组装成更复杂的对象或完整的对象。后一种情况经常发生在考古发掘现场，那里的物品被发现是碎片，或者已经被侵蚀损坏。尽管最近在计算机视觉的自动场景恢复方面取得了实质性进展，但自由形状提取和组装所带来的挑战仍然很大。研究人员将采用一种交互式方法，用户可以指导恢复过程，也可以在机器请求帮助时提供帮助，例如，在组装许多碎片以重新创建大型或复杂对象的复杂任务中。其目的是开发用户控制技术的基本原理，以使幼稚的用户受益。最终目标是通过对底层3D结构进行建模来提高与大量复杂视觉数据交互的生产力。这个项目将提供新的实用工具。它还将为3D形状重建和识别提供一个有效的测试平台，为处理3D形状提供更多描述性的局部和全局模型，更好地理解人类/决策-机器交互的自由几何建模，以及从一个或多个图像和视频中提取3D几何，以及相关的计算复杂性问题。应用于考古领域，这项技术将提供改进的测量方法，先进的考古记录和一种进行高水平分析的手段，这是迄今为止没有的。它将进一步允许将重建能力从艺术家直接转移到考古学家。由于在考古背景下解决的问题在很大程度上是通用的，因此可以转移到医学、工业、国防等领域，因此潜在的影响是非常广泛的。

With National Science Foundation support Dr David Cooper and his colleagues will develop a technology for the recovery of 3D free-form object and selected scene structure from one or more images and video. The technique is based on the development of 3D shape representation and a semi-interactive, mixed-initiative system, along with machine decision-directed Bayesian surface-estimation. The main focus of the effort is the development of tools useful in archaeological site and artifact reconstruction and architecture. This will impact low level shape models and how they are assembled to form either more complex objects or complete ones. The latter condition often occurs at archaeological excavation sites where objects are found in pieces, or have been damaged from erosion. Despite recent substantial progress in automated scene recovery in computer vision, the challenges presented by free-form shape extraction and assembly are still great. The researchers will employ an interactive approach in which a user can guide the recovery process or can be available when requested for assistance by the machine, e.g., in the complex task of assembling many fragments to re-create a large or complicated object. The intent is to develop the fundamentals of a user-controlled technology for the benefit of the naive user. The ultimate goal is to enhance productivity in interacting with large amounts of complex visual data by modeling the underlying 3D structure.This project will provide new practical tools. It will also provide an effective testbed for 3D shape reconstruction and recognition, more descriptive local and global models for working with 3D shapes, a better understanding of human/decision-making-machine interaction for free-form geometric modeling and for extracting 3D geometry from one or more images and video, and associated computational complexity issues. As applied to the field of archaeology, this technology will provide improved surveying methods, an advanced archaeological record and a means to conduct high-level analysis not heretofore available. It will further permit the transfer of reconstruction capabilities from the artist directly to the archaeologist. Since the problems resolved in the archaeological context are to a significant degree generic and thus transferable to the fields of medicine, industry, defense etc, the potential impact is extremely broad.