期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2012
卷号：3
期号：3-2
出版社：Seventh Sense Research Group
摘要：Photograph sear reconstruct methods usually fail to capture the user’s intention when the query termism ambiguous. Therefore, reconstruct with user interactions, or active reconstruct, is highly demanded to effect very improve the search performance. The essential problem in active reconstruct is how to target the user’s intention. To complete this goal, this paper presents a structural information based sample selection strategy to reduce the user’s labeling efforts. Furthermore, to localize the user’s intention in the visual feature e space, a novel localglobal discriminative dimension reduction algorithmic proposed. In this algorithm, a sub manifold is leer need by transferring the local geometry and the discriminate vet information from the labeled photographs to the whole (global) photograph database. Experiments on both synthetic datasets and a real Network photograph sear chdatasetde menstruate he effectiveness of the proposed active reconstruct scheme, including both the structural information based active sample selection strategy and the localglobal discriminative dimension reduction algorithm.
关键词：Active reconstructs; local-global discriminative (LGD) dimension reduction; structural information (SInfo) based active sample selection; network photograph sear reconstruct
