Self-similarity representation of Weber faces for kinship classification
Citations
1 citations
Cites background from "Self-similarity representation of W..."
...Unlike most previous kinship verification work where low-level hand-crafted feature descriptors [12, 13, 15, 24, 34, 39, 47, 48, 50, 53, 54] such as local binary pattern (LBP) [2, 9] and Gabor features [31, 54] are employed for face representation, we expect to extract more semantic information from low-level features to better characterize the relation of face images for kinship verification....
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1 citations
Additional excerpts
...[10] çalışmasında, Weber yüzlerin özgün benzerlik gösterimi (self similarity representation of Weber face) önerilmektedir....
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1 citations
Additional excerpts
...EQ-TARGET;temp:intralink-;e004;116;216 S 0ðmc;mn; tÞ 1⁄4 8< : 1; mn > mc þ t 0; mn > mc − t and mn < mc þ t −1; mn < mc − t ; (4)...
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1 citations
Cites background or methods from "Self-similarity representation of W..."
..., Cor nellKin [5], VB KinFace [7], IIITD Kinship [18], Fam ily101 [12], KinFaceW-I [13], KinFaceW-II [13], TSKin Face [35], etc....
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...[18] Local feature representation image 2012 Somanath el at....
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...Representative such fea ture information include skin color [5], histogram of gradien t [5, 6, 11], Gabor wavelet [7, 10, 11, 23], gradient orientation pyramid [10], local binary pattern [13], scale-invariant feature transform [11, 13, 15], salient part [8, 9], self-similarity [18], and dynamic features combined with spatio-temporal appear ance descriptor [19]....
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...While these methods have achieved some encouraging performance [5-13, 15, 18], it is still challenging to develop discriminative and robust kinship verification approaches for real-world applications, especially when face images are captured in unconstrained environments where large variations of pose, illumination, expression, and background occur....
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...UB KinFace [7] lIITD Kinship [18] Family101 [12] KinFaceW-I [13] KinFaceW-I [13] TSKinFace [35] KFV W (Ours)...
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References
31,952 citations
"Self-similarity representation of W..." refers background in this paper
...75% which was comparatively better than Local Binary Pattern (LBP) [1], Histogram of Gradients (HOG) [4], Principal Component Analysis (PCA) [8], and Linear Embedding (LE) [2]....
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...The authors reported an accuracy of 67.75% which was comparatively better than Local Binary Pattern (LBP) [1], Histogram of Gradients (HOG) [4], Principal Component Analysis (PCA) [8], and Linear Embedding (LE) [2]....
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26,531 citations
"Self-similarity representation of W..." refers methods in this paper
...The χ(2) distance measures (in a vector form) are provided as input to the SVM classifier [11] with the classes being kin and non-kin....
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18,620 citations
"Self-similarity representation of W..." refers methods in this paper
...The face region present in the image is first extracted using the Adaboost face detector [12]....
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8,504 citations
"Self-similarity representation of W..." refers methods in this paper
...Therefore, Difference of Gaussian (DoG) approach [7] has been applied to extract these features using the steps below....
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5,563 citations
"Self-similarity representation of W..." refers background in this paper
...75% which was comparatively better than Local Binary Pattern (LBP) [1], Histogram of Gradients (HOG) [4], Principal Component Analysis (PCA) [8], and Linear Embedding (LE) [2]....
[...]
...The authors reported an accuracy of 67.75% which was comparatively better than Local Binary Pattern (LBP) [1], Histogram of Gradients (HOG) [4], Principal Component Analysis (PCA) [8], and Linear Embedding (LE) [2]....
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