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Comparative Analysis of Decision-level Fusion Algorithms for 3D Face Recognition

B. Gokberk, L. Akarun
2006 18th International Conference on Pattern Recognition (ICPR'06)  
3D shape-based face recognition algorithms can be improved by using decision-level fusion algorithms.  ...  In this work, we present a comparative analysis of various fusion algorithms, and also propose novel ones.  ...  Conclusion In this paper, we review and compare various decisionlevel fusion architectures, and also propose novel ones for 3D face recognition.  ... 
doi:10.1109/icpr.2006.387 dblp:conf/icpr/GokberkA06 fatcat:zo74yog5yvb7xjr5lyax5trjvq

Multi Modal Face Recognition Using Block Based Curvelet Features [article]

Jyothi K, Prabhakar C.J
2014 arXiv   pre-print
Further, computed decision scoresof intensity and depth map are combined at decision level to improve the face recognition rate.  ...  The 3D surface of face (Depth Map) is computed from the stereo face images using stereo vision technique.  ...  Face recognition algorithms are categorized into 1) 2D face recognition, 2) 3D face recognition and 3) multimodal face recognition algorithms (2D and 3D facial data).  ... 
arXiv:1405.2641v2 fatcat:usbebo6ee5d6hepneb7imuad2u

Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels [chapter]

Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei
2005 Lecture Notes in Computer Science  
In this paper, we propose a systematic framework for fusing 2D and 3D face recognition at both feature and decision levels, by exploring synergies of the two modalities at these levels.  ...  This leads to a matching engine for 3D face recognition. Second, we propose a statistical learning approach for fusing 2D and 3D based face recognition at both feature and decision levels.  ...  Conclusion In this paper, we explore synergies of 3D and 2D modalities by proposing a systematic framework for fusing 2D and 3D face recognition at both feature and decision levels.  ... 
doi:10.1007/11564386_5 fatcat:wfpklacpxfhk5i56b6jfmlbzgq

Integrating shape and color cues for textured 3D object recognition

Yulan Guo, Ferdous A. Sohel, Mohammed Bennamoun, Jianwei Wan, Min Lu
2013 2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA)  
3D object recognition is a fundamental research topic. However, shape only feature descriptors for 3D object recognition have been the main focus of research.  ...  The C-RoPS descriptor is based on the color space instead of the 3D shape coordinates. We then use feature level and decision level fusion approaches to combine the shape and color information.  ...  This strategy essentially selects the class output of the most reliable pattern classifier and is provn to perform well for decision level fusion based 3D face recognition [3] .  ... 
doi:10.1109/iciea.2013.6566627 fatcat:w4d2adnucfh25fsnwgkhi3ov2e

Optimal Linear Combination of Facial Regions for Improving Identification Performance

Kin-Chung Wong, Wei-Yang Lin, Yu Hen Hu, Nigel Boston, Xueqin Zhang
2007 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
This paper presents a novel 3D multiregion face recognition algorithm that consists of new geometric summation invariant features, and an optimal linear feature fusion method.  ...  Experiments on the FRGC (Face Recognition Grand Challenge) V2.0 dataset show that this new algorithm improves the recognition performance significantly in the presence of facial expressions.  ...  In this work, we propose a novel multi-region face recognition algorithm for 3D face recognition.  ... 
doi:10.1109/tsmcb.2007.895325 pmid:17926697 fatcat:5enqpyakv5dcxbge5xtnoljnaa

Next Level of Data Fusion for Human Face Recognition [article]

Mrinal Kanti Bhowmik, Gautam Majumdar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri
2011 arXiv   pre-print
This paper demonstrates two different fusion techniques at two different levels of a human face recognition process.  ...  The first one is called data fusion at lower level and the second one is the decision fusion towards the end of the recognition process.  ...  ACKNOWLEDGMENT Authors are thankful to a major project entitled "Design and Development of Facial Thermogram Technology for Biometric Security System," at Department of Computer Science and Engineering  ... 
arXiv:1106.3466v1 fatcat:ykrx2boc7bfbpnap2fof6bn5ba

3D face recognition by projection-based methods

Helin Dutagaci, Bülent Sankur, Yücel Yemez, Edward J. Delp III, Ping Wah Wong
2006 Security, Steganography, and Watermarking of Multimedia Contents VIII  
In this paper, we investigate recognition performances of various projection-based features applied on registered 3D scans of faces.  ...  The block-based local features are fused both at feature level and at decision level. The resulting feature vectors are matched using Linear Discriminant Analysis.  ...  Figure 8 : 8 Sample block-based feature vector obtained from fusion at feature level. Figure 9 : 9 Procedure for fusion at feature level. Figure 10 : 10 Procedure for fusion at decision level.  ... 
doi:10.1117/12.643089 dblp:conf/sswmc/DutagaciSY06 fatcat:mks2uxmpurewfdwhrggpsujdee

State of the art in infrared face recognition

Moulay Akhloufi, Abdelhakim Bendada, Jean-Christophe Batsale
2008 Quantitative InfraRed Thermography Journal  
Face recognition is an area that has attracted a lot of interest. Much of the research in this field was conducted using visible images.  ...  In this paper we give an overview of the state of the art in face recognition using infrared images. Emphasis is given to more recent works.  ...  ., 2003b describe a fusion of visible and infrared images for face recognition. Image fusion is performed at data and decision levels ( Figure 15 ).  ... 
doi:10.3166/qirt.5.3-26 fatcat:xc5gd2qqdnfqjph6ovxhek7aae

3D Face Recognition For Biometric Applications

Lale Akarun, Berk Gokberk, Albert Ali Salah
2005 Zenodo  
Publication in the conference proceedings of EUSIPCO, Antalya, Turkey, 2005  ...  The outputs of these pattern classifiers are merged using a rank-based decision level fusion algorithm.  ...  decision level.  ... 
doi:10.5281/zenodo.39327 fatcat:6culz2fkhbf37gugu66uackzp4

3D and Thermo-Face Fusion [chapter]

Stepan Mracek, Jan Vana, Radim Dvorak, Martin Drahansky, Svetlana Yanushkevich
2012 New Trends and Developments in Biometrics  
CZ and N"TO Collaborative Linkage Grant C"P.E"P.CLG Intelligent assistance systems multisensor processing and reliability analysis.  ...  Author details Štěpán Mráček , Jan Váňa , Radim Dvořák , Martin Drahanský and Svetlana Yanushkevich Faculty of Information Technology, "rno University of Technology, Czech Republic University of Calgary  ...  We illustrate concept of fusion at the recognition component, which is a part of more complex decision-making level.  ... 
doi:10.5772/51991 fatcat:rkoamrb3tfa4ljliieeamlj56u

A Proposed Integrated Human Recognition for Security Reassurance

Fatma Susilawati Mohamad, Zahraddeen Sufyanu, Ahmad Salihu Ben-Musa
2015 American Journal of Applied Sciences  
In addition, two fusion strategies namely, score-level and decision-level are presented using robust algorithms.  ...  This research proclaims a new technique of integration for human recognition improvement using four physiological characteristics: Face, iris, palmprint and thumbprint.  ...  The corresponding author thanks the Kano State Government Nigeria, for providing the scholarship.  ... 
doi:10.3844/ajassp.2015.155.165 fatcat:xfxak6jzjzdghnrtytvvoegfri

Introducing FoxFaces: A 3-in-1 Head Dataset

Amel Aissaoui, Afifa Dahmane, Jean Martinet, Ioan Marius Bilasco
2016 Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications  
Hence, our dataset can be an interesting resource for the evaluation of 2D, 3D and bimodal algorithms on face recognition under adverse conditions as well as facial expression recognition and pose estimation  ...  We introduce a new test collection named FoxFaces, dedicated to researchers in face recognition and analysis.  ...  The bi-level fusion, which combines 2D, 3D and early fusion decisions, proves to be better than the three other strategies used separately.  ... 
doi:10.5220/0005714405330537 dblp:conf/visapp/AissaouiDMB16 fatcat:l3bo67kb5rcgznndrj7ek6pjle

Review on Face, Ear and Signature for Human Identification

Suvarnsing G., Sumegh Tharewal, Hanumant Gite, Siddharth Dabhade, K. V.
2018 International Journal of Computer Applications  
In this paper, we discuss different methods of Face, Ear and signature for recognition and identification.  ...  The concert rate of unimodal biometric is frequently reduced due to the user mode and physiological defects. We have referred papers related to face, ear and signature.  ...  The minimum distance rule (MDR) is adopt for fusion of the match score level and compare the outcome of the multimodality recognition with the results of the unimodal palmprint and face recognition.  ... 
doi:10.5120/ijca2018916250 fatcat:g5bxxtbqtnc6jl6tjhqz3f5lgm

Automatic 3D face recognition from depth and intensity Gabor features

Chenghua Xu, Stan Li, Tieniu Tan, Long Quan
2009 Pattern Recognition  
In our system, all processes are performed automatically, thus providing a prototype of automatic face recognition combining depth and intensity information.  ...  In this paper, we investigate what contributions depth and intensity information makes to face recognition when expression and pose variations are taken into account, and we propose a novel system for  ...  The fully automatic implementation in this work also provides a promising way to build a robust recognition system integrating depth and intensity information.  ... 
doi:10.1016/j.patcog.2009.01.001 fatcat:vfhkqbar3vaa3oo53h7g47ayxy

Face Recognition using 3D Facial Shape and Color Map Information: Comparison and Combination [article]

Afzal Godil, Sandy Ressler, Patrick Grother
2011 arXiv   pre-print
In this paper, we investigate the use of 3D surface geometry for face recognition and compare it to one based on color map information.  ...  We also discuss the different techniques for the combination of the 3D surface and color map information for multi-modal recognition by using different fusion approaches and show that there is significant  ...  We would also like to thank Qiming Wang of NIST for her help during this project.  ... 
arXiv:1105.2797v1 fatcat:nnzltxindrg7la7jvgy7f3k3s4
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