Fast verification via statistical geometric for mobile visual search

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• 作者：Miaohui Zhang ; Shaozi Li ; Xianming Lin ; Songzhi Su ; Rongrong Ji
• 刊名：Multimedia Systems
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：22
• 期：4
• 页码：525-534
• 全文大小：3,468 KB
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Operating Systems
  Data Storage Representation
  Data Encryption
  Computer Graphics
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-1882
• 卷排序：22

文摘

In this paper, an efficient geometric statistics method is proposed to obtain the geometric information of the object, which can achieve fast visual re-ranking along with the localization of target-of-interest. Given an input pair of images, first we get a set of interest-point correspondences, and enumerate all potential pairs in each image, upon which we calculate the statistics of the corresponding pairs to yield the geometric similarity score. We use a location geometric similarity scoring method that is invariant to rotation, scale, and translation, and can be easily incorporated in mobile visual search and augmented reality systems. Then fitting the statistics of geometric similarity scores into a Gaussian distribution that is used as a priori to determine the matching. The performance of our geometric scoring scheme is compared to the conventional geometric scoring schemes using orientation and scale. It is shown that our proposed statistically geometric method can generate fast geometric re-ranking. Meanwhile, we can accurately locate the target of search interest regardless of variations caused by occlusion and perspective changes.KeywordsMobile visual searchStatistics geometricObject locationBoW