作者: Substance-Abuse 時(shí)間: 2025-3-21 22:24 作者: Encapsulate 時(shí)間: 2025-3-22 01:28
Non-negative Compatible Kernel Construction for Face Recognitionalled the nonnegative in-compatible problem of KNMF. To tackle this problem, this paper presents a new methodology to construct Nonnegative Compatible Kernel (NC-Kernel) for face recognition. We obtain a Nonnegative Nonlinear Mapping (NN-Mapping) by using the techniques of symmetric NMF and nonnegat作者: 相互影響 時(shí)間: 2025-3-22 07:47 作者: browbeat 時(shí)間: 2025-3-22 11:57 作者: RECUR 時(shí)間: 2025-3-22 14:01
Block Statistical Features-based Face Verification on Second Generation Identity Cardttention. This paper proposes a block statistical features(BSF) learning method combining with local Gabor binary pattern(LGBP) for face verification in both second generation identity card(2nd ID card) and video set, which show many differences in biometric caused by age gap and image acquisition c作者: MANIA 時(shí)間: 2025-3-22 20:21
Towards Practical Face Recognition: A Local Binary Pattern Non Frontal Faces Filtering Approachecognition accuracy, in order to solve these problems, we propose non frontal faces filter’s method via support vector machine(SVM) and local binary patterns(LBP). By this method the images with large pose deflection will be filtered. Firstly, we apply the AdaBoost algorithm into real-time face dete作者: 露天歷史劇 時(shí)間: 2025-3-22 23:17 作者: happiness 時(shí)間: 2025-3-23 05:16 作者: harrow 時(shí)間: 2025-3-23 08:59
Nonlinear Metric Learning with Deep Convolutional Neural Network for Face Verifications, one is face representation and the other is the similarity computation of face vectors. Addressing the two problem, this paper proposes a method for simultaneously learning features and a corresponding similarity metric for a real world face verification, which apply novel regularization to learn作者: IRATE 時(shí)間: 2025-3-23 11:21 作者: 露天歷史劇 時(shí)間: 2025-3-23 15:55
A DCNN and SDM Based Face Alignment Algorithm existing all the time in face alignment: the initialization and great accuracy difference between inner points and outline points. First, we adopt DCNN to coarsely localize 5 points: two pupils, nose and two mouth corners. Second, based on shape initialization of coarse location, using SDM with ext作者: 確定方向 時(shí)間: 2025-3-23 21:50 作者: AORTA 時(shí)間: 2025-3-24 00:06 作者: perjury 時(shí)間: 2025-3-24 03:06 作者: Coronary 時(shí)間: 2025-3-24 09:07
Non-negative Sparsity Preserving Projections Algorithm Based Face Recognitionpose a more reasonable method of constructing the weight matrix and the coefficients of the weight matrix are all non-negative. This method is more consistent with the biological modeling of visual data and often produces much better results for data representation. Experimental results have shown t作者: 吸氣 時(shí)間: 2025-3-24 11:50 作者: Jocose 時(shí)間: 2025-3-24 16:19
Heterogeneous Face Recognition Based on Super Resolution Reconstruction by Adaptive Multi-dictionarya super resolution reconstruction algorithm by adaptive multi-dictionary learning is adopted. Compared with the traditional global dictionary learning, this algorithm spends less time on dictionary training and image reconstruction to a great extent. Firstly, a sketch is transformed to a photo by ei作者: 奴才 時(shí)間: 2025-3-24 20:12
Jinfeng Yang,Jucheng Yang,Jianjiang FengIncludes supplementary material: 作者: Ointment 時(shí)間: 2025-3-25 00:39
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188169.jpg作者: humectant 時(shí)間: 2025-3-25 03:18
Riitta Kosunen,Maria Frick,Jaana Koluotient Image method with 3D Generic Elastic Models (AQI-GEM). Frontal, neutral light face is re-rendered virtually under varying illumination conditions by AQI. Nearly accurate 3D models are constructed from each re-rendered image by GEM so as to virtually synthesize images under varying poses and i作者: Biguanides 時(shí)間: 2025-3-25 09:20
Jukka Mettovaara,Jussi Ylikoskiudies on face liveness detection have been performed. In this paper, we cast the face liveness detection problem as a classification problem to distinguish the images of true faces and photo samples based on the rank analysis of sample matrices. We assume that the rank of the true face sample matrix作者: 通便 時(shí)間: 2025-3-25 14:11 作者: 許可 時(shí)間: 2025-3-25 17:01 作者: Proclaim 時(shí)間: 2025-3-25 22:59
https://doi.org/10.1007/978-981-10-7239-0ction methods with the help of standalone filter learning and multiscale local feature combination. Such structure cascaded by both linear layers with convolution filters and non-linear layers in binarization process shows better adaptability in different databases. With the help of parallel computi作者: 其他 時(shí)間: 2025-3-26 03:16 作者: 女上癮 時(shí)間: 2025-3-26 06:52 作者: 殘暴 時(shí)間: 2025-3-26 10:10 作者: MIRTH 時(shí)間: 2025-3-26 13:52
Theoretical Framework of the Study,ave shown satisfying performance on most benchmark datasets. However, its representation is huge. In this paper, we present a novel approach to make Fisher vector compact and improves its performance. We utilize handcrafted low-level descriptors as FV do. However, we retain only 1st order statistics作者: 開花期女 時(shí)間: 2025-3-26 20:03
https://doi.org/10.1007/978-981-10-7239-0s, one is face representation and the other is the similarity computation of face vectors. Addressing the two problem, this paper proposes a method for simultaneously learning features and a corresponding similarity metric for a real world face verification, which apply novel regularization to learn作者: 能夠支付 時(shí)間: 2025-3-27 00:28 作者: GNAW 時(shí)間: 2025-3-27 04:56 作者: Canyon 時(shí)間: 2025-3-27 08:14 作者: GRACE 時(shí)間: 2025-3-27 09:40
https://doi.org/10.1007/978-981-10-7239-0t method, we appropriately choose a larger step-length than that of traditional NMF and obtain efficient NMF update rules with fast convergence rate and high performance. The step-length is determined by solving some inequalities, which are established according to the requirements on step-length an作者: 拱墻 時(shí)間: 2025-3-27 15:32
Dopls: A new type of programming language,to in such a scenario lacking of information to predict the variations of the query sample. We propose a novel method patch-based sparse dictionary representation (PSDR) to tackle the problem of various variations e.g. expressions, illuminations, corruption, occlusion and disguises in FR with SSPP. 作者: MAIM 時(shí)間: 2025-3-27 21:14 作者: 共棲 時(shí)間: 2025-3-28 01:04
Birna Arnbj?rnsdóttir,Hafdís Ingvarsdóttirork has revealed that some algorithms based on image descriptors are applied to face liveness detection against face spoofing attacks, such as LBP and LBP-TOP. However, these image descriptors are not robust to spoofing attacks. In this paper, we propose a robust and powerful local descriptor, calle作者: 舉止粗野的人 時(shí)間: 2025-3-28 05:08 作者: MERIT 時(shí)間: 2025-3-28 08:40 作者: JOT 時(shí)間: 2025-3-28 11:52
978-3-319-25416-6Springer International Publishing Switzerland 2015作者: nautical 時(shí)間: 2025-3-28 16:57
Biometric Recognition978-3-319-25417-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 不愛防注射 時(shí)間: 2025-3-28 21:19
Theoretical Framework of the Study,n kernel to the LSSVM algorithm, proposing a robust face detection algorithm. Extensive experiments on the widely used CMU+MIT dataset and FDDB dataset demonstrate the robustness and validity of our algorithm.作者: 圖表證明 時(shí)間: 2025-3-29 00:47
Robust Face Detection Based on Enhanced Local Sensitive Support Vector Machinen kernel to the LSSVM algorithm, proposing a robust face detection algorithm. Extensive experiments on the widely used CMU+MIT dataset and FDDB dataset demonstrate the robustness and validity of our algorithm.作者: ineluctable 時(shí)間: 2025-3-29 06:23 作者: sparse 時(shí)間: 2025-3-29 09:22 作者: Amendment 時(shí)間: 2025-3-29 11:47 作者: Bernstein-test 時(shí)間: 2025-3-29 16:14
Jukka Mettovaara,Jussi Ylikoski is much higher than that of the photo sample matrix under an ideal situation. If we denoise the real world samples and convert them into pure samples, we can find a well boundary, that is, a basis for liveness detection. Experiments are conducted on the NUAA imposter database to verify the efficiency of the proposed method.作者: –吃 時(shí)間: 2025-3-29 21:31 作者: expound 時(shí)間: 2025-3-30 03:45
Theoretical Framework of the Study,onditions. To alleviate computation complexity of Gabor transformation, we exploit energy check Gabor filters to speed up calculation. Specially, the verification rate of our approach on NEU-ID database achieves 97.71?%. It has a comparable performance with lower computation complexity.作者: Commonplace 時(shí)間: 2025-3-30 05:08
Theoretical Framework of the Study, of FV, introduce Gaussian block to sparsify FV, alter its formulation, and normalize properly. We evaluate our method on LFW and FERET dataset, and result shows our method effectively compresses Fisher vector and achieves satisfying result at the same time.作者: bromide 時(shí)間: 2025-3-30 10:46
Theoretical Framework of the Study,racting simplified SIFT features, we finely localizes 49 inner points and 17 outline points. Experiments on CAS-PEAL-R1 and FERET database show that our approach is accurate and robust. The proposed method achieves 99.23% localization accuracy of eyes on CAS-PEAL-R1.作者: 情愛 時(shí)間: 2025-3-30 13:45 作者: 無動(dòng)于衷 時(shí)間: 2025-3-30 19:38 作者: FOVEA 時(shí)間: 2025-3-30 21:37
Language Corpora Annotation and Processingalgorithm. The proposed face recognition method is evaluated on CASIA 3D face database. And the experimental results show our approach has superior performance than many existing methods for 3D face recognition and handles pose variations quite well.作者: 悶熱 時(shí)間: 2025-3-31 01:12
Theoretical Framework of the Study,ator. Finally, SVM is used to classify frontal and non frontal faces. Experimental results show that the proposed method has good classification capability for face images with varying pose. It contribute to eliminate the impact of pose variation in dynamic face recognition system.作者: 看法等 時(shí)間: 2025-3-31 08:39 作者: 流動(dòng)才波動(dòng) 時(shí)間: 2025-3-31 12:47
https://doi.org/10.1007/978-981-10-7239-0ilar Subspace (LCRC_SS), which changes the projective space from global space to local similarity subspace. The main advantages lie in LCRC_SS are making full use of “similar” resources and discarding the redundant “dissimilar” images in CR. Extensive experiments show that LCRC_SS has better recognition rate than CRC.作者: annexation 時(shí)間: 2025-3-31 15:42 作者: 鄙視讀作 時(shí)間: 2025-3-31 19:36 作者: 肉身 時(shí)間: 2025-3-31 23:46
Birna Arnbj?rnsdóttir,Hafdís Ingvarsdóttirur new SYSU-MFSD database demonstrate that the descriptor can achieve a better liveness detection performance in both intra and cross-databases compared to the state-of-the-art techniques based on descriptors.作者: Panacea 時(shí)間: 2025-4-1 02:21
Language Development and Assessmentto, which is able to enhance the quality of synthesized photo effectively. Finally, the synthesized photo is recognized by two-dimensional marginal fisher analysis. We demonstrate these ideas in practice and show how they lead to faster operation speed and ideal recognition rate.作者: 圍裙 時(shí)間: 2025-4-1 07:28
Non-negative Compatible Kernel Construction for Face Recognitionly the NC-Kernel to the Kernel Principle Component Analysis (KPCA) and KNMF for face recognition. The ORL and Pain Expression face databases are selected for evaluations. Experimental results indicate our NC-Kernel based methods outperform some RBF or polynomial kernel based algorithms.作者: ADOPT 時(shí)間: 2025-4-1 13:53 作者: Rotator-Cuff 時(shí)間: 2025-4-1 15:04
Towards Practical Face Recognition: A Local Binary Pattern Non Frontal Faces Filtering Approachator. Finally, SVM is used to classify frontal and non frontal faces. Experimental results show that the proposed method has good classification capability for face images with varying pose. It contribute to eliminate the impact of pose variation in dynamic face recognition system.作者: 苦澀 時(shí)間: 2025-4-1 19:12
Metric Learning Based False Positives Filtering for Face Detectionearning, we adopt a batch-stochastic gradient descent scheme, with which we can get stable solution fast. The results on FDDB and our self-collected dataset show a good performance of our method for improving Viola-Jones face detectors.
