WISE: Large Scale Web Image Search and Exploration

Our goal is to build a web-scale content based image retrieval system. We are addressing two major challenges by harnessing the distributed computing power in MSR-SVC: 1) large scale machine learning for image representation and , 2) efficient image indexing and query. The following are several ongoing projects within WISE.

Content-Based Image Retrieval. We have developed scalable image representations and algorithms for both indexing and retrieval for content-based image retrieval. This technology has been transferred to Bing to enable indexing and searching billions of images by content, which has various applications. One feature released in Bing is "Find more sizes" where a user can find different sizes of near and partial duplicates of a given image.

Large-Scale Face Image Retrieval. Face images are popular on the web. We have developed customized face features and indexgen/indexserve pipelines to enable web-scale face image recognition and retrieval.

ImageGraph: Large-Scale Image Clustering. Our goal is to clustering the whole web images. As a first step, we have developed an efficient hashing scheme to discovering partial-duplicate web images.

Publications

Interns
  Zhong Wu (2008,2009), David Lee (2009), Jia Deng (2010), Yunchao Gong (2011)