Feature Group Utility in Model-Based 3D Object Recognition Systems

计算机视觉中要求最高的应用之一是 基于模型的3D物体识别 这些系统通常使用 识别图像中对象的对应技术;集合 在场景特征组之间形成绑定（例如， 点、曲线、曲面或体积）和兼容的 模型特征 的辨别能力（或效用） 单个特征（例如点、曲线、曲面或体积） 和兼容的模型特征组。 的歧视 这些功能组中的各个功能组的能力（或效用） 系统是计算机视觉中一个具有挑战性的重要问题 research. 当识别系统被期望选择 从数百或数千个数据库中校正模型， 索引方法（快速拒绝模型的子集 数据库）是有用的，或者 如果要有效地识别物体， 特征组的使用提供了一种有前途的技术， 执行此索引任务。 本研究调查了特征组的两个方面 效用概念：从 输入图像，以及由其产生的特征的对称布置 数据库中对象模型的固有对称性。 初步的实验结果也被描述。 具体 拟议研究的目标是（a）将显着性 和对称概念的坚实的理论基础，（B）推广 用于识别显著和对称特征的现有技术 组超出其当前域（多面体或二次曲面 表面变成更有表现力和更通用的特征类， 及（c）扩充现有超过100个目标模型的数据库， 包括附加、更真实的对象。

One of the most demanding applications in computer vision is model-based 3D object recognition. Such systems often use correspondence techniques to identify objects in an image; sets of bindings are formed between groups of scene features (e.g., points, curves, surfaces, or volumes) and compatible groups of model features. The discrimination ability ( or utility) of individual features (e.g. points, curves, surfaces, or volumes) and compatible groups of model features. The discrimination ability (or utility) of individual feature groups in these systems is a challenging and important problem in computer vision research. When recognition systems are expected to select the correct model(s) out of a database of hundreds or thousands, indexing methods (which quickly reject a subset of the model database from further consideration by the system) are useful or often essential if objects are to be recognized efficiently, and the use of feature groups offers a promising technique for performing this indexing task. This research investigates two facets of the feature group utility concept: saliency of feature groups extracted from the input image, and symmetric arrangements of features arising from inherent symmetries of the object models in the database. Preliminary experimental results are also described. Specific goals of the proposed research are to (a) place both the saliency and symmetry concepts on a firm theoretical basis, (b) generalize existing techniques for identifying salient and symmetric feature groups out of their current domain (of polyhedral or quadric surfaces into more expressive and generic classes of features, and (c) expand a current database of over 100 object models to include additional, more realistic objects.