Time and Space-Efficient Template Based Indexing

基于时间和空间高效模板的索引

• 批准号: 9907142
• 负责人: Martial Hebert
• 金额: $ 27.98万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9907142&HistoricalAwards=false
• 关键词: Time; Space; Efficient; Template; Based

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.

摘要IIS-9907142 Hebert，MartialCarnegie Mellon University $93，733 - 12 mos。时间和空间有效的基于模板的索引这是一个为期三年的连续奖项的第一年资助。根据该奖项，PI将开发一种基于图像的对象识别方法，直接解决对象识别问题所带来的基本挑战：对姿态和照明变化的敏感性，相对于模型的数量和复杂性的计算复杂性，和潜在的禁止的存储要求表示的模型。该方法是基于计算的响应适当的过滤器的图像中的模型对象和观察到的场景。根据这项资助进行的研究涉及数学建模的过滤器，具有理想的属性方面的变化，姿态和照明。在可能的滤波器类中，由于它们相对于图像变换组的特性，可操纵滤波器类被用作这种分析的起点。这些属性被用来开发一个有效的indexingscheme识别。这项研究的主要贡献是一个有效的和强大的方法来匹配和索引，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，这项研究将有助于可操纵滤波器的计算理论，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。