基于哈希的图像搜索技术

基于哈希的图像搜索技术第一期提纲背景典型方法评价指标总结背景图片搜索引擎移动搜索业务皮革纺织医学背景为什么要用哈希？背景怎样对图像特征进行哈希编码？背景…背景…110110010110001000000001…背景110110010110001000000001……Hammingdistance:14……背景背景100001110111000101DatasetSimplehashtable背景100001110111000101DatasetQ110111SimplehashtableXOR背景100001110111000101<<NQDatasetSearchthehashtableforasmallsetofimages.Q110111SimplehashtableXOR背景背景特征进行哈希编码的本质？背景Gionis,A.&Indyk,P.&Motwani,R.(1999)TakerandomprojectionsofdataQuantizeeachprojectionwithfewbits010101101NolearninginvolvedGistdescriptor典型方法

局部敏感哈希

LocalSensitiveHashingTheprobabilitythatarandom

hyperplaneseparatestwounitvectorsdependsontheanglebetweenthem:[GoemansandWilliamson1995,Charikar2004,modifiedbyme]Highdotproduct:unlikelytosplitLowerdotproduct:likelytosplitCorrespondinghashfunction:典型方法

局部敏感哈希

LocalSensitiveHashingGroundTruth32bit128bitALSHfamily,H(c,r,P1,P2),foranyp,qbelongtoS,If||p-q||≤r,thenPr(h(p)=h(q))≥P1If||p-q||≥cr,thenPr(h(p)=h(q))≤P2256bit典型方法

局部敏感哈希

LocalSensitiveHashing典型方法

局部敏感哈希

LocalSensitiveHashing典型方法

迭代量化编码

IterativeQuantizationAveragequantizationerror:1.00(a)PCAaligned.Averagequantizationerror:0.93(b)RandomRotation.Averagequantizationerror:0.88(c)OptimizedRotation.Q(B,R)=||B-VR||F2100001111110000101001011[1].S.

Lazebnik,A.Gordo,andF.Perronnin,“IterativeQuantization:AProcrusteanApproachtoLearningBinaryCodesforLarge-scaleImageRetrieval,”Accepted,IEEETrans.PatternAnalysisandMachineLearningIntelligence,2012.典型方法

迭代量化编码

IterativeQuantization[1].S.

Lazebnik,A.Gordo,andF.Perronnin,“IterativeQuantization:AProcrusteanApproachtoLearningBinaryCodesforLarge-scaleImageRetrieval,”Accepted,IEEETrans.PatternAnalysisandMachineLearningIntelligence,2012.典型方法

迭代量化编码

IterativeQuantizationRRITQ32bitLSHPCAH典型方法

迭代量化编码

IterativeQuantization典型方法迭稀疏迭代量化编码

SparseProjectionsforHigh-DimensionalBinaryCodes[1].Y.Xia,K.He,P.Kohli,andJ.

Sun,“SparseProjectionsforHigh-DimensionalBinaryCodes,”inCVPR,2015.典型方法

核监督哈希

SupervisedHashingwithKernels[1].W.Liu,W.Jun,R.Ji,Y.Jiang,andS.Chang,“Supervisedhashingwithkernels,”Proc.IEEECo