Online Sketching Hashing
Leng, Cong1; Wu, Jiaxiang1; Cheng, Jian1; Bai, Xiao2; Lu, Hanqing1
2015
会议名称CVPR2015
会议录名称IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
会议日期2015
会议地点USA
摘要
Recently, hashing based approximate nearest neighbor (ANN) search has attracted much attention. Extensive new algorithms have been developed and successfully applied to
different applications. However, two critical problems are rarely mentioned. First, in real-world applications, the data often comes in a streaming fashion but most of existing hashing methods are batch based models. Second, when the dataset becomes huge, it is almost impossible to load all the data into memory to train hashing models. In this paper, we propose a novel approach to handle these two problems simultaneously based on the idea of data sketching. A sketch of one dataset preserves its major characters but with significantly smaller size. With a small size sketch, our method can learn hash functions in an online fashion, while needs rather low computational complexity and storage space.
Extensive experiments on two large scale benchmarks and one synthetic dataset demonstrate the efficacy of the proposed method.
关键词Sketching
收录类别EI
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11785
专题模式识别国家重点实验室_图像与视频分析
通讯作者Cheng, Jian
作者单位1.中科院自动化研究所
2.北京航空航天大学
推荐引用方式
GB/T 7714
Leng, Cong,Wu, Jiaxiang,Cheng, Jian,et al. Online Sketching Hashing[C],2015.
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