Time and Space-Efficient Template Based Indexing

iis -9907142赫伯特，军事，卡耐基梅隆大学$93,733 - 12。时间和空间高效的基于模板的索引这是一项为期三年的持续奖励的第一年资助。根据该合同，PI将开发一种基于图像的物体识别方法，直接解决物体识别问题带来的基本挑战：对姿态和光照变化的敏感性，与模型数量和复杂性相关的计算复杂性，以及表示模型的潜在令人望而却步的存储要求。该方法基于计算模型对象和观察场景图像中适当滤波器的响应。在这项资助下进行的研究涉及对滤镜的数学建模，这些滤镜在姿势和照明的变化方面具有理想的特性。在可能的滤波器类别中，可控制滤波器类别被用作本分析的起点，因为它们具有关于图像变换组的特性。利用这些特性开发了一种高效的识别索引方案。本研究的主要贡献是提供了一种有效且稳健的匹配和索引方法，可以直接用于识别，也可以与其他识别技术（如基于特征的技术）结合使用。此外，该研究将有助于可操纵滤波器的计算理论，该理论将滤波器的数学特性转换为与广泛的识别，图像匹配和图像分析问题相关的算法。

Abstract IIS-9907142Hebert, MartialCarnegie Mellon University$93,733 - 12 mos.Time and Space-Efficient Template Based IndexingThis is the first year funding of a three year continuing award. Under this award, the PI will develop an approach to image-based object recognition which directly addressesthe fundamental challenges posed by the object recognition problem: sensitivity to changes in pose and illumination, computational complexity with respect to the number and complexity of the models, and potentially prohibitive storage requirement for representing the models.The approach is based on computing the responses ofappropriate filters in images of the model objects and of the observed scenes. The research conducted under this grant involves the mathematical modelingof filters that have desirable properties with respect to changes in pose and illumination. Amongst the possible classes of filter, the class of steerable filters is usedas a starting point for this analysis, owing to their properties with respect to groups of image transformations. These properties are exploited to develop an efficient indexingscheme for recognition. The main contribution of this research is an efficient and robust approach to matching and indexing which may be used directly for recognition, and also may be used in conjunction with other recognition techniques, such as feature-based techniques. In addition, the research will contribute to a computational theory of steerable filters which will convert the mathematical properties of the filters to algorithms relevant to a broad range of recognition, image matching, and image analysis problems.