Knowledge Commons of Institute of Automation,CAS
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 | 紫东太初大模型研究中心_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 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Leng, Cong,Wu, Jiaxiang,Cheng, Jian,et al. Online Sketching Hashing[C],2015. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
CVPR2015_Online Sket(250KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论