AnnoSearch: Image Auto-Annotation by Search
- 10 July 2006
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 1483-1490
- https://doi.org/10.1109/cvpr.2006.58
Abstract
Although it has been studied for several years by computer vision and machine learning communities, image annotation is still far from practical. In this paper, we present AnnoSearch, a novel way to annotate images using search and data mining technologies. Leveraging the Web-scale images, we solve this problem in two-steps: 1) searching for semantically and visually similar images on the Web, 2) and mining annotations from them. Firstly, at least one accurate keyword is required to enable text-based search for a set of semantically similar images. Then content-based search is performed on this set to retrieve visually similar images. At last, annotations are mined from the descriptions (titles, URLs and surrounding texts) of these images. It worth highlighting that to ensure the efficiency, high dimensional visual features are mapped to hash codes which significantly speed up the content-based search process. Our proposed approach enables annotating with unlimited vocabulary, which is impossible for all existing approaches. Experimental results on real web images show the effectiveness and efficiency of the proposed algorithm.Keywords
This publication has 8 references indexed in Scilit:
- Photo-to-searchPublished by Association for Computing Machinery (ACM) ,2005
- A database centric view of semantic image annotation and retrievalPublished by Association for Computing Machinery (ACM) ,2005
- Hidden Markov models for automatic annotation and content-based retrieval of images and videoPublished by Association for Computing Machinery (ACM) ,2005
- Searching the web with mobile images for location recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Learning to cluster web search resultsPublished by Association for Computing Machinery (ACM) ,2004
- Confidence-based dynamic ensemble for image annotation and semantics discoveryPublished by Association for Computing Machinery (ACM) ,2003
- Modeling annotated dataPublished by Association for Computing Machinery (ACM) ,2003
- 10.1162/153244303322533214Applied Physics Letters, 2000