计算机与现代化
計算機與現代化
계산궤여현대화
COMPUTER AND MODERNIZATION
2015年
6期
41-45
,共5页
王琪%杜娟%程彬%徐国清
王琪%杜娟%程彬%徐國清
왕기%두연%정빈%서국청
高斯核%混合核%SIFT%最大最小聚类%协作式标注%垃圾标签
高斯覈%混閤覈%SIFT%最大最小聚類%協作式標註%垃圾標籤
고사핵%혼합핵%SIFT%최대최소취류%협작식표주%랄급표첨
Gaussian kernel%mixed-kernel%SIFT%max-min cluster%collaborative annotation%spam tag
由于用户标签的不准确和语义模糊使得协作式标注图像检索正确率低,而现有垃圾标签过滤方法往往关注标签本身,忽略了协作式标签与图像的关联性。本文在分析协作式标注图像视觉内容与标签的关联性的基础上,提出一种基于协作式标注图像视觉内容的垃圾标签检测方法。该方法分析同一标签下图像视觉内容,设计不同的核函数用于颜色和SIFT( Scale-invariant feature transform)特征子集,同时将2种低维特征映射到高维多模特征空间形成混合核函数,对同一标签下的图像进行基于混合核的最大最小距离聚类,少数群体的标签说明与图像内容关联性小则为用户标注错误的标签,从而检测垃圾标签。实验结果表明,该方法能够提高协作式图像垃圾标签检测的正确性。
由于用戶標籤的不準確和語義模糊使得協作式標註圖像檢索正確率低,而現有垃圾標籤過濾方法往往關註標籤本身,忽略瞭協作式標籤與圖像的關聯性。本文在分析協作式標註圖像視覺內容與標籤的關聯性的基礎上,提齣一種基于協作式標註圖像視覺內容的垃圾標籤檢測方法。該方法分析同一標籤下圖像視覺內容,設計不同的覈函數用于顏色和SIFT( Scale-invariant feature transform)特徵子集,同時將2種低維特徵映射到高維多模特徵空間形成混閤覈函數,對同一標籤下的圖像進行基于混閤覈的最大最小距離聚類,少數群體的標籤說明與圖像內容關聯性小則為用戶標註錯誤的標籤,從而檢測垃圾標籤。實驗結果錶明,該方法能夠提高協作式圖像垃圾標籤檢測的正確性。
유우용호표첨적불준학화어의모호사득협작식표주도상검색정학솔저,이현유랄급표첨과려방법왕왕관주표첨본신,홀략료협작식표첨여도상적관련성。본문재분석협작식표주도상시각내용여표첨적관련성적기출상,제출일충기우협작식표주도상시각내용적랄급표첨검측방법。해방법분석동일표첨하도상시각내용,설계불동적핵함수용우안색화SIFT( Scale-invariant feature transform)특정자집,동시장2충저유특정영사도고유다모특정공간형성혼합핵함수,대동일표첨하적도상진행기우혼합핵적최대최소거리취류,소수군체적표첨설명여도상내용관련성소칙위용호표주착오적표첨,종이검측랄급표첨。실험결과표명,해방법능구제고협작식도상랄급표첨검측적정학성。
The accuracy of the collaborative tagging image retrieval is lower because of the inaccuracy of user’ s annotation. Exist-ing spam tag detection methods tend to focus on label itself, ignoring the correlation between collaborative label and image. Ana-lyzing the correlation of collaborative tagging image visual content and image tags, the spam tag detection method of collaboration annotation based on visual content of collaborative tagging image is proposed. The method analyze visual content of images which have the same tag and design different kernel functions for color and SIFT feature subset. The two features will be mapped form low dimensional space to high dimensional character space, while the mixed-kernel function is established. Finally, the images which have the same tag is clustered by max-min distance means, and the tag of images in the class which has a few images are spam tags because of weak correlation. The experimental results show that the method can improve the accuracy of the tag spam detection on collaborative annotation images.