RIA: Robust 3D Object Recognition Using Uncertain 2D Image Data

9309100营地这是一个为期三年的连续奖励的第一年。 该研究使用的技术，从强大的统计加上贝叶斯方法，开发数学模型，从不确定的2D图像数据的强大的3D对象识别，并开发匹配方案，使用这些模型来鲁棒地识别和计算对象的姿态，同时提供了一个措施的置信水平的假设。 这些结果应该使计算机视觉系统的发展，可以科普不完善的真实的输入数据，由于例如碎片或传感器噪声，而不诉诸于使用特设的算法或试错程序。 这样的系统应该提供更强大的性能和显着降低开发成本。

9309100 Camps This is the first year of a three-year continuing award. The research uses techniques from robust statistics coupled with a Bayesian approach, to develop mathematical models for robust 3D object recognition from uncertain 2D image data, and to develop matching schemes that use these models to robustly recognize and compute the pose of an object, while providing a measure of confidence level for the hypothesis made. The results should enable development of computer vision systems that can cope with imperfections in real input data, due for example to fragmentation or sensor noise, without resorting to use of ad hoc heuristics or trial-and-error procedures. Such systems should offer more robust performance and significant reductions in development cost.