Data-Dependent Hashing Based on p-Stable Distribution
文献类型：期刊论文
| 作者 | Bai, Xiao1; Yang, Haichuan1; Zhou, Jun2; Ren, Peng3; Cheng, Jian4
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| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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| 出版日期 | 2014-12-01 |
| 卷号 | 23期号:12页码:5033-5046 |
| 关键词 | Image retrieval hash retrieval p-stable distribution |
| 英文摘要 | The p-stable distribution is traditionally used for data-independent hashing. In this paper, we describe how to perform data-dependent hashing based on p-stable distribution. We commence by formulating the Euclidean distance preserving property in terms of variance estimation. Based on this property, we develop a projection method, which maps the original data to arbitrary dimensional vectors. Each projection vector is a linear combination of multiple random vectors subject to p-stable distribution, in which the weights for the linear combination are learned based on the training data. An orthogonal matrix is then learned data-dependently for minimizing the thresholding error in quantization. Combining the projection method and orthogonal matrix, we develop an unsupervised hashing scheme, which preserves the Euclidean distance. Compared with data-independent hashing methods, our method takes the data distribution into consideration and gives more accurate hashing results with compact hash codes. Different from many data-dependent hashing methods, our method accommodates multiple hash tables and is not restricted by the number of hash functions. To extend our method to a supervised scenario, we incorporate a supervised label propagation scheme into the proposed projection method. This results in a supervised hashing scheme, which preserves semantic similarity of data. Experimental results show that our methods have outperformed several state-of-the-art hashing approaches in both effectiveness and efficiency. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | QUANTIZATION ; CODES |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000344481700002 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3341]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 作者单位 | 1.Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China 2.Griffith Univ, Sch Informat & Commun Technol, Nathan, Qld 4111, Australia 3.China Univ Petr, Coll Informat & Control Engn, Qingdao 257061, Peoples R China 4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bai, Xiao,Yang, Haichuan,Zhou, Jun,et al. Data-Dependent Hashing Based on p-Stable Distribution[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2014,23(12):5033-5046. |
| APA | Bai, Xiao,Yang, Haichuan,Zhou, Jun,Ren, Peng,&Cheng, Jian.(2014).Data-Dependent Hashing Based on p-Stable Distribution.IEEE TRANSACTIONS ON IMAGE PROCESSING,23(12),5033-5046. |
| MLA | Bai, Xiao,et al."Data-Dependent Hashing Based on p-Stable Distribution".IEEE TRANSACTIONS ON IMAGE PROCESSING 23.12(2014):5033-5046. |
入库方式： OAI收割
来源：自动化研究所
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