Face anti-spoofing with multifeature videolet aggregation
Citations
12 citations
Cites methods from "Face anti-spoofing with multifeatur..."
...Table 1 shows the EER and HTER of advanced face antispoofing methods: the LBP+HOOF based mothod [20], the IDA based method [3], the color analysis based methods [5, 2] and the dynamic texture based mothd [13]....
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...Method EER HTER EER LBP+HOOF [20] - - 3....
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12 citations
12 citations
11 citations
Cites background from "Face anti-spoofing with multifeatur..."
...In general, passive methods are based on analyzing different facial properties, such as frequency content [28, 46], texture [2, 12, 17, 27, 32, 53] and quality [18, 21, 23], or motion cues, such as eye blinking [3, 38, 45, 47], facial expression changes [3, 25, 45, 47], mouth movements [3, 25, 45, 47], or even color variation due to blood circulation (pulse) [15, 29, 31], to discriminate face artifacts from genuine ones....
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11 citations
Cites methods from "Face anti-spoofing with multifeatur..."
...[4] suggested a face antispoofing approach based on multi feature Videolet aggregation inspired from the fact of combining the evidence obtained from textural and motional information which were extracted from the face region and its surroundings....
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...[4] Multi feature videolet aggregation SVM CASIA EER=3....
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References
2,653 citations
"Face anti-spoofing with multifeatur..." refers background in this paper
...Dynamic texture features such as LBP-TOP [22] are studied in this regard....
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1,709 citations
"Face anti-spoofing with multifeatur..." refers background in this paper
...Biometric systems have different points of vulnerability such as sensor attacks, overriding feature extraction, tampering feature representation, corrupting matcher, tampering stored template, and overriding decision [18]....
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899 citations
"Face anti-spoofing with multifeatur..." refers methods in this paper
...The orientation based optical flow vector is computed by solving the optimization problem 1 using conjugate gradient method [12]....
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716 citations
"Face anti-spoofing with multifeatur..." refers background or methods in this paper
...• On MSU dataset, HOOF obtains tremendous improvement in EER (from 30.41 to 2.50...
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...Similarly, at the Inter Feature Fusion stage, the correlation of 0.51, 0.62, and 0.66 is observed for CASIA, MSU, and 3DMAD datasets, respectively....
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...MSU dataset contains a higher fraction of replay attack videos compared to CASIA....
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...• Performance of the Proposed Approach: The proposed fusion approach (using HOOF and multi-LBP with face and scene aggregated over videolets) provides 0% EER with uncontrolled illumination and background on both MSU and 3DMAD datasets....
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...Orthogonal to the LBP texture descriptors based approaches, quality assessment metrics such as specular reflection, blurring and color density are also explored for anti-spoofing [10], [20]....
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707 citations
Additional excerpts
...The face anti-spoofing problem is extensively studied in literature, particularly with the introduction of Print Attack dataset [1], Replay Attack dataset [5], CASIA-FASD spoofing dataset [21], 3DMAD database [7], and MSU mobile face spoofing database [20]....
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