Image-Based Accurate Object Retrieval Combined with Color Invariant
Finding information based on an objects profile is very useful when exact keywords for the object are unknown. Current image retrieval system all ignores the color information, for example we want to find a super-star with a piece of red petticoat, or we want to a red flower with white background. They all cannot give the desired results in state of the art image search engine. We have developed an object retrieval system that takes images of objects as queries and finds relevant image scenes that contain the objects, which combined with the color information. We supply a query object by selecting a region of the query image, and the system returns a ranked list of images that contain the same object. We use Caltech-1011 as test queries. Creating an image-fcature vocabulary is a time-consuming process, and it affects the performance. To address those problems we compare many scalable methods for building the vocabulary tree and introduce n fast adaptive method combined with color information, which we show outperforms the current famous systems.
Content-based Image Retrieval color-invariant vocabulary tree SIFT vector space model
Yuzheng Cui Baihua Xiao
The key Laboratory of Complex System and Intelligence Science Institute of Automation Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190, BEIJING, CHINA
国际会议
长沙
英文
1648-1651
2010-05-11（万方平台首次上网日期，不代表论文的发表时间）