22.2.2.7 Face Recognition from Video, Faces in Video

Chapter Contents (Back)
Face Recognition. Application, Faces. Application, Face Recognition. Video Analysis. Video Face Recognition. A subset:
See also Face Recognition from Video, Faces in Video, Chellappa Group Papers.
See also Face Detection in Video.

Lucas, S.M.,
Continuous n-tuple classifier and its application to real-time face recognition,
VISP(145), No. 5, October 1998, pp. p.343. BibRef 9810
Earlier:
Face recognition with the continuous n-tuple classifier,
BMVC97(xx-yy).
HTML Version. BibRef

Lucas, S.M., Huang, T.K.[Tzu-Kuo],
Sequence recognition with scanning N-tuple ensembles,
ICPR04(III: 410-413).
IEEE DOI 0409
BibRef

Eickeler, S.[Stefan], Müller, S.[Stefan], Rigoll, G.[Gerhard],
Recognition of JPEG compressed face images based on statistical methods,
IVC(18), No. 4, March 2000, pp. 279-287.
Elsevier DOI 0003
BibRef
Earlier:
High Quality Face Recognition in JPEG Compressed Images,
ICIP99(I:672-676).
IEEE DOI BibRef

Steffens, J.B.[Johannes Bernhard], Elagin, E.V.[Egor Valerievich], Nocera, L.P.A.[Luciano Pasquale Agostino], Maurer, T.[Thomas], Neven, H.[Hartmut],
Face recognition from video images,
US_Patent6,301,370, October 9, 2001
WWW Link. BibRef 0110

Maurer, T.[Thomas], Elagin, E.V.[Egor Valerievich], Nocera, L.P.A.[Luciano Pasquale Agostino], Steffens, J.B.[Johannes Bernhard], Neven, H.[Hartmut],
Wavelet-based facial motion capture for avatar animation,
US_Patent6,272,231, Aug 7, 2001
WWW Link. BibRef 0108
And: US_Patent6,580,811, Jun 17, 2003
WWW Link. BibRef

Raytchev, B.[Bisser], Murase, H.[Hiroshi],
Unsupervised recognition of multi-view face sequences based on pairwise clustering with attraction and repulsion,
CVIU(91), No. 1-2, July-August 2003, pp. 22-52.
Elsevier DOI 0309
BibRef
Earlier:
VQ-Faces: Unsupervised Face Recognition from Image Sequences,
ICIP02(II: 809-812).
IEEE DOI 0210
BibRef
Earlier:
Unsupervised Face Recognition from Image Sequences,
ICIP01(I: 1042-1045).
IEEE DOI 0108
BibRef
And:
Unsupervised Face Recognition from Image Sequences Based on Clustering with Attraction and Repulsion,
CVPR01(II:25-30).
IEEE DOI 0110

See also Unsupervised face recognition by associative chaining. BibRef

Raytchev, B.[Bisser], Kimura, Y.[Yusuke], Yoda, I.[Ikushi], Sakaue, K.[Katsuhiko],
Real-time 3D head pose estimation using both geometry and learning,
ICIP10(1525-1528).
IEEE DOI 1009
BibRef

Hadid, A.[Abdenour], Pietikäinen, M.[Matti],
An Experimental Investigation about the Integration of Facial Dynamics in Video-Based Face Recognition,
ELCVIA(5), No. 1, March 2005, pp. 1-13.
DOI Link BibRef 0503
Earlier:
From Still Image to Video-Based Face Recognition: An Experimental Analysis,
AFGR04(813-818).
IEEE DOI 0411

See also Face Description with Local Binary Patterns: Application to Face Recognition. BibRef

Hadid, A.[Abdenour], Pietikainen, M.[Matti],
A Hybrid Approach to Face Detection under Unconstrained Environments,
ICPR06(I: 227-230).
IEEE DOI 0609
BibRef

Hadid, A.[Abdenour], Pietikäinen, M.[Matti], Li, S.Z.[Stan Z.],
Learning Personal Specific Facial Dynamics for Face Recognition from Videos,
AMFG07(1-15).
Springer DOI 0710
BibRef

Hadid, A.[Abdenour], Dugelay, J.L.[Jean-Luc], Pietikäinen, M.[Matti],
On the use of dynamic features in face biometrics: Recent advances and challenges,
SIViP(5), No. 4, November 2011, pp. 495-506.
WWW Link. 1111
BibRef

Arandjelovic, O.D.[Ognjen D.], Cipolla, R.[Roberto],
An information-theoretic approach to face recognition from face motion manifolds,
IVC(24), No. 6, 1 June 2006, pp. 639-647.
Elsevier DOI 0606
BibRef
Earlier:
Face Recognition from Video Using the Generic Shape-Illumination Manifold,
ECCV06(IV: 27-40).
Springer DOI 0608
BibRef
Earlier:
Face Recognition from Face Motion Manifolds using Robust Kernel Resistor-Average Distance,
FaceVideo04(88).
IEEE DOI 0502
Face motion manifolds; Kernel; Resistor-average distance BibRef

Arandjelovic, O.D.[Ognjen D.], Cipolla, R.[Roberto],
Achieving robust face recognition from video by combining a weak photometric model and a learnt generic face invariant,
PR(46), No. 1, January 2013, pp. 9-23.
Elsevier DOI 1209
Manifold; Illumination; Pose; Motion; Invariance; Generic BibRef

Arandjelovic, O.D.[Ognjen D.], Cipolla, R.[Roberto],
A pose-wise linear illumination manifold model for face recognition using video,
CVIU(113), No. 1, January 2009, pp. 113-125.
Elsevier DOI 0812
BibRef
Earlier:
A New Look at Filtering Techniques for Illumination Invariance in Automatic Face Recognition,
FGR06(449-454).
IEEE DOI 0604
BibRef
Earlier:
An Illumination Invariant Face Recognition System for Access Control using Video,
BMVC04(xx-yy).
HTML Version. 0508
Face recognition; Manifolds; Illumination; Pose; Robustness; Invariance; Video BibRef

Arandjelovic, O.D.[Ognjen D.],
Computationally efficient application of the generic shape-illumination invariant to face recognition from video,
PR(45), No. 1, January 2012, pp. 92-103.
Elsevier DOI 1109
BibRef
Earlier:
Accurate and Efficient Face Recognition from Video,
BMVC10(xx-yy).
HTML Version. 1009
Lighting; Pose; Signature; Warp; Mixture; Manifold BibRef

Arandjelovic, O.D.[Ognjen D.],
Gradient Edge Map Features for Frontal Face Recognition under Extreme Illumination Changes,
BMVC12(12).
DOI Link 1301
BibRef

Arandjelovic, O.D.[Ognjen D.],
Colour invariants under a non-linear photometric camera model and their application to face recognition from video,
PR(45), No. 7, July 2012, pp. 2499-2509.
Elsevier DOI 1203
Face; Recognition; Colour; Invariant; Video BibRef

Arandjelovic, O.D.[Ognjen D.],
Making the most of the self-quotient image in face recognition,
FG13(1-7)
IEEE DOI 1309
error statistics BibRef

Arandjelovic, O.D.[Ognjen D.], Cipolla, R.[Roberto],
A methodology for rapid illumination-invariant face recognition using image processing filters,
CVIU(113), No. 2, February 2009, pp. 159-171.
Elsevier DOI 0901
Face recognition; Illumination; Invariance; Filters; Video; Image processing BibRef

Arandjelovic, O.D.[Ognjen D.], Hammoud, R.I.[Riad I.], Cipolla, R.[Roberto],
Thermal and reflectance based personal identification methodology under variable illumination,
PR(43), No. 5, May 2010, pp. 1801-1813.
Elsevier DOI 1003
BibRef
Earlier:
On Person Authentication by Fusing Visual and Thermal Face Biometrics,
AVSBS06(50-50).
IEEE DOI 0611
Face; Recognition; Thermal; Infrared; Fusion; Illumination; Invariance BibRef

Arandjelovic, O.D.[Ognjen D.], Hammoud, R.I.[Riad I.],
Multi-Sensory Face Biometric Fusion (for Personal Identification),
OTCBVS06(128).
IEEE DOI 0609
BibRef
And: Add A3: Cipolla, R.[Roberto], Biometrics06(52).
IEEE DOI 0609

See also Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems. BibRef

Arandjelovic, O.D.[Ognjen D.], Cipolla, R.[Roberto],
Colour invariants for machine face recognition,
FG08(1-8).
IEEE DOI 0809
BibRef
And:
Face Set Classification using Maximally Probable Mutual Modes,
ICPR06(I: 511-514).
IEEE DOI 0609
BibRef
And:
Incremental Learning of Temporally-Coherent Gaussian Mixture Models,
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Kim, T.K.[Tae-Kyun], Arandjelovic, O.D.[Ognjen D.], Cipolla, R.[Roberto],
Boosted manifold principal angles for image set-based recognition,
PR(40), No. 9, September 2007, pp. 2475-2484.
Elsevier DOI 0705
Face recognition; Manifolds; Image set; Principal angle; Canonical correlation analysis; Boosting; Nonlinear subspace; Illumination; Pose; Robustness; Invariance BibRef

Bonde, U.D.[Ujwal D.], Kim, T.K.[Tae-Kyun], Ramakrishnan, K.R.,
Randomised Manifold Forests for Principal Angle-Based Face Recognition,
ACCV10(IV: 228-242).
Springer DOI 1011
BibRef

Arandjelovic, O.D.[Ognjen D.], Shakhnarovich, G.[Gregory], Fisher, J.W.[John W.], Cipolla, R.[Roberto], Darrell, T.J.[Trevor J.],
Face Recognition with Image Sets Using Manifold Density Divergence,
CVPR05(I: 581-588).
IEEE DOI 0507
BibRef

Kim, T.K., Arandjelovic, O.D., Cipolla, R.,
Learning over Sets using Boosted Manifold Principal Angles (BoMPA),
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Singh, R.[Richa], Vatsa, M.[Mayank], Ross, A.A.[Arun A.], Noore, A.[Afzel],
A Mosaicing Scheme for Pose-Invariant Face Recognition,
SMC-B(37), No. 5, October 2007, pp. 1212-1225.
IEEE DOI 0711

See also Age Transformation for Improving Face Recognition Performance. BibRef

Matsui, A.[Atsushi], Clippingdale, S.[Simon], Matsumoto, T.[Takashi],
Pruned Resampling: Probabilistic Model Selection Schemes for Sequential Face Recognition,
IEICE(E90-D), No. 8, August 2007, pp. 1151-1159.
DOI Link 0708
BibRef
Earlier:
A Sequential Monte Carlo Method for Bayesian Face Recognition,
SSPR06(578-586).
Springer DOI 0608
BibRef

Matsui, A.[Atsushi], Clippingdale, S.[Simon], Matsumoto, T.[Takashi],
Bayesian sequential face detection with automatic re-initialization,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Matsui, A., Clippingdale, S., Uzawa, F., Matsumoto, T.,
Bayesian face recognition using a Markov chain Monte Carlo method,
ICPR04(III: 918-921).
IEEE DOI 0409
BibRef

Clippingdale, S.[Simon], Fujii, M.[Mahito],
Face Recognition for Video Indexing: Randomization of Face Templates Improves Robustness to Facial Expression,
VLBV03(32-40).
Springer DOI 0310
BibRef

Clippingdale, S.[Simon], Ito, T.[Takayuki],
A Unified Approach to Video Face Detection, Tracking and Recognition,
ICIP99(I:662-666).
IEEE DOI BibRef 9900

Huang, K.S.[Kohsia S.], Trivedi, M.M.[Mohan M.],
Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
BibRef
Earlier:
Streaming face recognition using multicamera video arrays,
ICPR02(IV: 213-216).
IEEE DOI 0211
BibRef

Everingham, M.R.[Mark R.], Zisserman, A.[Andrew],
Automated detection and identification of persons in video using a coarse 3D head model and multiple texture maps,
VISP(152), No. 6, December 2005, pp. 902-910.
DOI Link 0512
BibRef
Earlier:
Identifying Individuals in Video by Combining Generative and Discriminative Head Models,
ICCV05(II: 1103-1110).
IEEE DOI 0510
BibRef
Earlier:
Automated visual identification of characters in situation comedies,
ICPR04(IV: 983-986).
IEEE DOI 0409
BibRef
And:
Automated Person Identification in Video,
CIVR04(289-298).
Springer DOI 0505

See also Taking the bite out of automated naming of characters in TV video. BibRef

Everingham, M.R.[Mark R.], Sivic, J.[Josef], Zisserman, A.[Andrew],
Taking the bite out of automated naming of characters in TV video,
IVC(27), No. 5, 2 April 2009, pp. 545-559.
Elsevier DOI 0904
BibRef
Earlier:
Hello! My name is Buffy: Automatic Naming of Characters in TV Video,
BMVC06(III:899).
PDF File. 0609
BibRef
Earlier: A2, A1, A3:
Person Spotting: Video Shot Retrieval for Face Sets,
CIVR05(226-236).
Springer DOI 0507
Video indexing; Automatic annotation; Face recognition
See also Automated detection and identification of persons in video using a coarse 3D head model and multiple texture maps. BibRef

Sivic, J.[Josef], Everingham, M.R.[Mark R.], Zisserman, A.[Andrew],
'Who are you?' - Learning person specific classifiers from video,
CVPR09(1145-1152).
IEEE DOI 0906
BibRef

Hsieh, C.K.[Chao-Kuei], Lai, S.H.[Shang-Hong], Chen, Y.C.[Yung-Chang],
Expression-Invariant Face Recognition With Constrained Optical Flow Warping,
MultMed(11), No. 4, June 2009, pp. 600-610.
IEEE DOI 0905
BibRef
Earlier:
Integrated Expression-Invariant Face Recognition with Constrained Optical Flow,
PSIVT09(702-713).
Springer DOI 0901
BibRef

Choi, J.Y.[Jae Young], Ro, Y.M.[Yong Man], Plataniotis, K.N.[Konstantinos N.],
Color Face Recognition for Degraded Face Images,
SMC-B(39), No. 5, October 2009, pp. 1217-1230.
IEEE DOI 0906
BibRef
Earlier:
Feature subspace determination in video-based mismatched face recognition,
FG08(1-6).
IEEE DOI 0809
BibRef

Choi, J.Y.[Jae Young], Plataniotis, K.N.[Konstantinos N.], Ro, Y.M.[Yong Man],
Face Feature Weighted Fusion Based on Fuzzy Membership Degree for Video Face Recognition,
SMC-B(42), No. 4, August 2012, pp. 1270-1282.
IEEE DOI 1208
BibRef

Choi, J.Y.[Jae Young], Ro, Y.M.[Yong Man], Plataniotis, K.N.[Konstantinos N.],
Boosting Color Feature Selection for Color Face Recognition,
IP(20), No. 5, May 2011, pp. 1425-1434.
IEEE DOI 1104
BibRef

Choi, J.Y.[Jae Young], Ro, Y.M.[Yong Man], Plataniotis, K.N.[Konstantinos N.],
Color Local Texture Features for Color Face Recognition,
IP(21), No. 3, March 2012, pp. 1366-1380.
IEEE DOI 1203
BibRef

Lee, S.H.[Seung Ho], Choi, J.Y.[Jae Young], Ro, Y.M.[Yong Man], Plataniotis, K.N.[Konstantinos N.],
Local Color Vector Binary Patterns From Multichannel Face Images for Face Recognition,
IP(21), No. 4, April 2012, pp. 2347-2353.
IEEE DOI 1204
BibRef
Earlier: A1, A2, A4, A3:
Local color vector binary pattern for face recognition,
ICIP11(2997-3000).
IEEE DOI 1201
BibRef
Earlier: A2, A4, A3, Only:
Using colour local binary pattern features for face recognition,
ICIP10(4541-4544).
IEEE DOI 1009

See also Using color texture sparsity for facial expression recognition. BibRef

Lee, S.H.[Seung Ho], Ro, Y.M.[Yong Man],
Local age group modeling in unconstrained face images for facial age classification,
ICIP14(1395-1399)
IEEE DOI 1502
Facial age classification;face clustering;local age group model BibRef

Lee, S.H.[Seung Ho], Kim, H.[Hyungil], Ro, Y.M.[Yong Man],
A Comparative Study of Color Texture Features for Face Analysis,
CCIW13(265-280).
Springer DOI 1304
BibRef

Louis, W.[Wael], Plataniotis, K.N.,
Co-Occurrence of Local Binary Patterns Features for Frontal Face Detection in Surveillance Applications,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103
BibRef
Earlier:
Frontal face detection for surveillance purposes using dual Local Binary Patterns features,
ICIP10(3809-3812).
IEEE DOI 1009
BibRef

Choi, J.Y.[Jae Young], Ro, Y.M.[Yong Man], Plataniotis, K.N.[Konstantinos N.],
A comparative study of preprocessing mismatch effects in color image based face recognition,
PR(44), No. 2, February 2011, pp. 412-430.
Elsevier DOI 1011
BibRef
Earlier:
Image compression mismatch effect on color image based face recognition system,
ICIP09(4149-4152).
IEEE DOI 0911
Color-based face recognition; Color face image; Preprocessing mismatch; Image compression; Grayscale conversion; Color space conversion BibRef

Choi, J.Y.[Jae Young], de Neve, W.[Wesley], Ro, Y.M.[Yong Man], Plataniotis, K.N.[Konstantinos N.],
Automatic Face Annotation in Personal Photo Collections Using Context-Based Unsupervised Clustering and Face Information Fusion,
CirSysVideo(20), No. 10, October 2010, pp. 1292-1309.
IEEE DOI 1011

See also Semantic annotation of personal video content using an image folksonomy. BibRef

Choi, J.Y.[Jae Young], de Neve, W.[Wesley], Plataniotis, K.N.[Konstantinos N.], Ro, Y.M.[Yong Man],
Collaborative Face Recognition for Improved Face Annotation in Personal Photo Collections Shared on Online Social Networks,
MultMed(13), No. 1, 2011, pp. 14-28.
IEEE DOI 1102
BibRef

Sohn, H.[Hosik], Lee, D.[Dohyoung], de Neve, W.[Wesley], Plataniotis, K.N.[Konstantinos N.], Ro, Y.M.[Yong Man],
Contribution of Non-scrambled Chroma Information in Privacy-Protected Face Images to Privacy Leakage,
IWDW11(453-467).
Springer DOI 1208
BibRef

Zou, W.W.[Wei-Wen], Yuen, P.C.[Pong C.],
Discriminability and reliability indexes: Two new measures to enhance multi-image face recognition,
PR(43), No. 10, October 2010, pp. 3483-3493.
Elsevier DOI 1007
Face recognition; Multiple images; Discriminability index; Reliability index; Image assessment BibRef

Mian, A.S.[Ajmal S.],
Online Learning from Local Features for Video-Based Face Recognition,
PR(44), No. 5, May 2011, pp. 1068-1075.
Elsevier DOI 1101
BibRef
Earlier:
Unsupervised Learning from Local Features for Video-Based Face Recognition,
FG08(1-6).
IEEE DOI 0809
Online learning; Face recognition; Video-based face recognition; Local features; Clustering
See also On the Repeatability and Quality of Keypoints for Local Feature-based 3D Object Retrieval from Cluttered Scenes. BibRef

See, J.[John], Fauzi, M.F.A.[Mohammad Faizal Ahmad], Eswaran, C.[Chikkannan],
Fusing cluster-centric feature similarities for face recognition in video sequences,
PRL(34), No. 16, 2013, pp. 2057-2064.
Elsevier DOI 1310
BibRef
Earlier: A1, A3, Only:
Exemplar extraction using spatio-temporal hierarchical agglomerative clustering for face recognition in video,
ICCV11(1481-1486).
IEEE DOI 1201
Video-based face recognition. Improve recognition by video. BibRef

Gou, G., Huang, D., Wang, Y.,
Video face recognition via combination of real-time local features and temporal-spatial cues,
IET-CV(8), No. 4, August 2014, pp. 347-357.
DOI Link 1407
BibRef

Yeh, M.C.[Mei-Chen], Wu, W.P.[Wen-Po],
Clustering Faces in Movies Using an Automatically Constructed Social Network,
MultMedMag(21), No. 2, April 2014, pp. 22-31.
IEEE DOI 1407
Clustering BibRef

Cao, X.C.[Xiao-Chun], Zhang, C.Q.[Chang-Qing], Zhou, C.J.[Cheng-Ju], Fu, H.Z.[Hua-Zhu], Foroosh, H.,
Constrained Multi-View Video Face Clustering,
IP(24), No. 11, November 2015, pp. 4381-4393.
IEEE DOI 1509
face recognition BibRef

Ding, S.[Sihao], Li, Y.[Ying], Zhu, J.[Junda], Zheng, Y.F., Xuan, D.[Dong],
Sequential Sample Consensus: A Robust Algorithm for Video-Based Face Recognition,
CirSysVideo(25), No. 10, October 2015, pp. 1586-1598.
IEEE DOI 1511
BibRef
Earlier:
Robust video-based face recognition by sequential sample consensus,
AVSS13(336-341)
IEEE DOI 1311
face recognition BibRef

Dewan, M.A.A.[M. Ali Akber], Granger, E.[Eric], Marcialis, G.L.[Gian Luca], Sabourin, R., Roli, F.[Fabio],
Adaptive appearance model tracking for still-to-video face recognition,
PR(49), No. 1, 2016, pp. 129-151.
Elsevier DOI 1511
Biometrics BibRef

Leng, M.J.[Meng-Jun], Moutafis, P.[Panagiotis], Kakadiaris, I.A.[Ioannis A.],
Joint prototype and metric learning for image set classification: Application to video face identification,
IVC(58), No. 1, 2017, pp. 204-213.
Elsevier DOI 1703
BibRef
Earlier: A2, A1, A3:
Regression-based metric learning,
ICPR16(2700-2705)
IEEE DOI 1705
Fasteners, Learning systems, Linear programming, Measurement, Optimization, Shape, Training. Image set classification BibRef

He, R.[Ran], Tan, T.N.[Tie-Niu], Davis, L.S.[Larry S.], Sun, Z.A.[Zhen-An],
Learning Structured Ordinal Measures for Video Based Face Recognition,
PR(75), No. 1, 2018, pp. 4-14.
Elsevier DOI 1712
Ordinal measure BibRef

He, R.[Ran], Wu, X.[Xiang], Sun, Z.N.[Zhe-Nan], Tan, T.N.[Tie-Niu],
Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition,
PAMI(41), No. 7, July 2019, pp. 1761-1773.
IEEE DOI 1906
Face, Face recognition, Sensors, Databases, Training, Correlation, Feature extraction, Heterogeneous face recognition, feature representation BibRef

Li, J.W.[Jiang-Wei], Wang, Y.H.[Yun-Hong], Tan, T.N.[Tie-Niu],
Video-Based Face Recognition Using Earth Mover's Distance,
AVBPA05(229).
Springer DOI 0509
BibRef

Liu, L.[Liang], Wang, Y.H.[Yun-Hong], Tan, T.N.[Tie-Niu],
Multi-Eigenspace Learning for Video-Based Face Recognition,
ICB07(181-190).
Springer DOI 0708
BibRef
And:
Online Appearance Model Learning for Video-Based Face Recognition,
Biometrics07(1-7).
IEEE DOI 0706
BibRef

Fan, W.[Wei], Wang, Y.H.[Yun-Hong], Tan, T.N.[Tie-Niu],
Video-Based Face Recognition Using Bayesian Inference Model,
AVBPA05(122).
Springer DOI 0509
BibRef

Liu, W.[Wei], Wang, Y.H.[Yun-Hong], Li, S.Z., Tan, T.N.[Tie-Niu],
Nearest intra-class space classifier for face recognition,
ICPR04(IV: 495-498).
IEEE DOI 0409
BibRef

Zhang, G.X.[Guang-Xiao], He, R.[Ran], Davis, L.S.[Larry S.],
Jointly Learning Dictionaries and Subspace Structure for Video-Based Face Recognition,
ACCV14(III: 97-111).
Springer DOI 1504
BibRef

Kumar, R.M.S.[R. Mathusoothana S.],
Robust multi-view videos face recognition based on particle filter with immune genetic algorithm,
IET-IPR(13), No. 4, March 2019, pp. 600-606.
DOI Link 1903
BibRef

Masi, I.[Iacopo], Tran, A.T.[Anh Tuan], Hassner, T.[Tal], Sahin, G.[Gozde], Medioni, G.[Gérard],
Face-Specific Data Augmentation for Unconstrained Face Recognition,
IJCV(127), No. 6-7, June 2019, pp. 642-667.
Springer DOI 1906
BibRef

Kim, K., Yang, Z., Masi, I., Nevatia, R., Medioni, G.,
Face and Body Association for Video-Based Face Recognition,
WACV18(39-48)
IEEE DOI 1806
face recognition, video signal processing, body appearance, body association, data association problem, face identification, Videos BibRef

Cevikalp, H.[Hakan], Dordinejad, G.G.[Golara Ghorban],
Video Based Face Recognition by Using Discriminatively Learned Convex Models,
IJCV(128), No. 12, December 2020, pp. 3000-3014.
Springer DOI 2010
BibRef
Earlier:
Discriminatively Learned Convex Models for Set Based Face Recognition,
ICCV19(10122-10131)
IEEE DOI 2004
convex programming, face recognition, learning (artificial intelligence), matrix multiplication, Optimization BibRef

Uzun, B.[Bedirhan], Cevikalp, H.[Hakan], Saribas, H.[Hasan],
Deep Discriminative Feature Models (DDFMs) for Set Based Face Recognition and Distance Metric Learning,
PAMI(45), No. 5, May 2023, pp. 5594-5608.
IEEE DOI 2304
Face recognition, Measurement, Neural networks, Convolutional neural networks, Deep learning, common vector BibRef

Cevikalp, H., Yavuz, H.S.,
Fast and Accurate Face Recognition with Image Sets,
AMFG17(1564-1572)
IEEE DOI 1802
Computational modeling, Face, Face recognition, Manifolds, Measurement, Support vector machines, Training BibRef

Yalcin, M., Cevikalp, H., Yavuz, H.S.,
Towards Large-Scale Face Recognition Based on Videos,
VidSum15(1078-1085)
IEEE DOI 1602
Collaboration BibRef

Cevikalp, H., Yavuz, H.S., Triggs, B.,
Face Recognition Based on Videos by Using Convex Hulls,
CirSysVideo(30), No. 12, December 2020, pp. 4481-4495.
IEEE DOI 2012
Videos, Face recognition, Face, Computational modeling, Measurement, Support vector machines, Manifolds, Face recognition, binary hierarchical tree BibRef

Choi, Y.R.[Young Rok], Kil, R.M.[Rhee Man],
Face Video Retrieval Based on the Deep CNN With RBF Loss,
IP(30), 2021, pp. 1015-1029.
IEEE DOI 2012
Extract discriminative features with small storage space from face videos with large intra-class variations caused by different angle, illumination, and facial expression. Face video retrieval, convolutional neural network, loss function, radial basis function, metric learning BibRef

Rivero-Hernández, J.[Jacinto], Morales-González, A.[Annette], Denis, L.G.[Lester Guerra], Méndez-Vázquez, H.[Heydi],
Ordered Weighted Aggregation Networks for Video Face Recognition,
PRL(146), 2021, pp. 237-243.
Elsevier DOI 2105
Neural aggregation network, Ordered weighted average operator, Video face recognition BibRef

Bahroun, S.[Sahbi], Abed, R.[Rahma], Zagrouba, E.[Ezzeddine],
KS-FQA: Keyframe selection based on face quality assessment for efficient face recognition in video,
IET-IPR(15), No. 1, 2021, pp. 77-90.
DOI Link 2106
BibRef

Kim, H.[Hayeon], Lee, E.C.[Eun-Cheol], Seo, Y.[Yongseok], Im, D.H.[Dong-Hyuck], Lee, I.K.[In-Kwon],
Character Detection in Animated Movies Using Multi-Style Adaptation and Visual Attention,
MultMed(23), 2021, pp. 1990-2004.
IEEE DOI 2107
Motion pictures, Animation, Streaming media, Adaptation models, Visualization, Task analysis, Detectors, Image analysis, visual attention BibRef

Lopez-Lopez, E.[Eric], Pardo, X.M.[Xose M.], Regueiro, C.V.[Carlos V.],
Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition,
PR(131), 2022, pp. 108885.
Elsevier DOI 2208
Open-set face recognition, Incremental Learning, Self-updating, Adaptive biometrics, Video-surveillance BibRef

Bi, J.[Jiang], Wang, L.[Lidong], Han, Y.[Yu], Zhou, C.[Cheng],
Real-time face perception based encoding strategy optimization method for UHD videos,
IET-IPR(17), No. 9, 2023, pp. 2764-2779.
DOI Link 2307
data compression, encoding, face recognition, image processing, signal processing, video coding, visual perception BibRef

Wang, Y.J.[Yu-Jiang], Dong, M.Z.[Ming-Zhi], Shen, J.[Jie], Luo, Y.M.[Yi-Ming], Lin, Y.M.[Yi-Ming], Ma, P.C.[Ping-Chuan], Petridis, S.[Stavros], Pantic, M.[Maja],
Self-Supervised Video-Centralised Transformer for Video Face Clustering,
PAMI(45), No. 11, November 2023, pp. 12944-12959.
IEEE DOI 2310
BibRef


Kuang, C.[Chenyi], Kephart, J.O.[Jeffrey O.], Ji, Q.[Qiang],
AU-Aware Dynamic 3D Face Reconstruction from Videos with Transformer,
WACV24(6225-6235)
IEEE DOI 2404
Gold, Solid modeling, Correlation, Face recognition, Dynamics, Transformers, Algorithms, Biometrics, face, gesture, body pose, Video recognition and understanding BibRef

Liao, Z.Y.[Zi-Yan], Di, D.[Dening], Hao, J.S.[Jing-Song], Zhang, J.[Jiang], Zhu, S.L.[Shu-Lei], Yin, J.[Jun],
MMM-GCN: Multi-Level Multi-Modal Graph Convolution Network for Video-Based Person Identification,
MMMod23(I: 3-15).
Springer DOI 2304
BibRef

Zhang, X.Y.[Xin-Yi], Tie, Y.[Yun], Qi, L.[Lin], Zhang, R.Z.[Rui-Zhe], Cai, J.J.[Juan-Juan],
Face Recognition Based on Panoramic Video,
FG21(1-7)
IEEE DOI 2303
Face recognition, Gesture recognition, Streaming media, Distortion, Real-time systems, Task analysis BibRef

El Hadi, M.L.[Moulay Lhabib], Nasri, M.[M'Barek], Farhaoui, Y.[Yousef], Ellaoui, A.[Ahmad],
Application of the deep learning approach for identification and face recognition in real-time video,
ISCV22(1-6)
IEEE DOI 2208
Deep learning, Training, Histograms, Face recognition, Streaming media, Real-time systems, Robustness, Facial recognition, deep learning BibRef

Hörmann, S.[Stefan], Cao, Z.X.[Zhen-Xiang], Knoche, M.[Martin], Herzog, F.[Fabian], Rigoll, G.[Gerhard],
Face Aggregation Network for Video Face Recognition,
ICIP21(2973-2977)
IEEE DOI 2201
Image recognition, Face recognition, Aggregates, Benchmark testing, Feature extraction, Generative adversarial networks, Biometrics BibRef

Li, F.T.[Fang-Tao], Wang, W.Z.[Wen-Zhe], Liu, Z.H.[Zi-He], Wang, H.R.[Hao-Ran], Yan, C.H.[Cheng-Hao], Wu, B.[Bin],
Frame Aggregation and Multi-Modal Fusion Framework for Video-Based Person Recognition,
MMMod21(I:75-86).
Springer DOI 2106
BibRef

Zhao, H.[He], Shi, Y.J.[Yong-Jie], Tong, X.[Xin], Wen, J.[Jingsi], Ying, X.H.[Xiang-Hua], Zha, H.B.[Hong-Bin],
G-FAN: Graph-Based Feature Aggregation Network for Video Face Recognition,
ICPR21(1672-1678)
IEEE DOI 2105
Correlation, Face recognition, Aggregates, Memory management, Benchmark testing, Predictive models, Feature extraction BibRef

Lopez-Lopez, E.[Eric], Regueiro, C.V.[Carlos V.], Pardo, X.M.[Xose M.],
An Adaptive Video-to-Video Face Identification System Based on Self-Training,
ICPR21(2590-2596)
IEEE DOI 2105
Support vector machines, Learning systems, Adaptation models, Data privacy, Adaptive systems, Face recognition BibRef

Kacem, A.[Anis], Ben Abdesslam, H.[Hamza], Cherenkova, K.[Kseniya], Aouada, D.[Djamila],
Space-time Triplet Loss Network for Dynamic 3d Face Verification,
3DHU20(82-90).
Springer DOI 2103
BibRef

Shabayek, A.E.R., Aouada, D., Cherenkova, K.[Kseniya], Gusev, G.[Gleb],
3D Sparse Deformation Signature for Dynamic Face Recognition,
ICIP20(2835-2839)
IEEE DOI 2011
Sparse 3D Deformation Signature, Lie Bodies, 3D Dynamic Face Recognition BibRef

Kim, M., Lee, H.J., Lee, S., Ro, Y.M.,
Robust Video Facial Authentication With Unsupervised Mode Disentanglement,
ICIP20(1321-1325)
IEEE DOI 2011
Deep learning, disentangled representation, facial authentication, dynamic encoding BibRef

Shim, M.H.[Min-Ho], Ho, H.I.[Hsuan-I], Kim, J.Y.[Jinh-Yung], Wee, D.Y.[Dong-Yoon],
READ: Reciprocal Attention Discriminator for Image-to-Video Re-identification,
ECCV20(XIV:335-350).
Springer DOI 2011
Compares a single query image to videos in the gallery. BibRef

Lee, H., Lee, J., Ng, J.Y., Natsev, P.,
Large Scale Video Representation Learning via Relational Graph Clustering,
CVPR20(6806-6815)
IEEE DOI 2008
Measurement, Training, Task analysis, Google, Marine vehicles, Clustering algorithms, Face recognition BibRef

Tapaswi, M., Law, M., Fidler, S.,
Video Face Clustering With Unknown Number of Clusters,
ICCV19(5026-5035)
IEEE DOI 2004
face recognition, learning (artificial intelligence), pattern clustering, video signal processing, Target tracking BibRef

Ma, Y.,
Effective Methods for Lightweight Image-Based and Video-Based Face Recognition,
LFR19(2683-2688)
IEEE DOI 2004
convolutional neural nets, face recognition, image sensors, learning (artificial intelligence), video signal processing, lightweight BibRef

Peng, B., Jin, X., Wu, Y., Li, D.,
Geometry Guided Feature Aggregation in Video Face Recognition,
LFR19(2670-2677)
IEEE DOI 2004
face recognition, feature extraction, video signal processing, geometry-based feature aggregation method, deep learning BibRef

Liu, Z., Hu, H., Bai, J., Li, S., Lian, S.,
Feature Aggregation Network for Video Face Recognition,
RLQ19(990-998)
IEEE DOI 2004
convolutional neural nets, face recognition, image representation, learning (artificial intelligence), attention BibRef

Hörmann, S., Knoche, M., Babaee, M., Köpüklü, O., Rigoll, G.,
Outlier-Robust Neural Aggregation Network for Video Face Identification,
ICIP19(1675-1679)
IEEE DOI 1910
video face recognition, face identification, biometrics, feature aggregation BibRef

Lopez-Lopez, E.[Eric], Regueiro, C.V.[Carlos V.], Pardo, X.M.[Xosé M.], Franco, A.[Annalisa], Lumini, A.[Alessandra],
Incremental Learning Techniques Within a Self-updating Approach for Face Verification in Video-Surveillance,
IbPRIA19(II:25-37).
Springer DOI 1910
BibRef

Parchami, M.[Mostafa], Bashbaghi, S.[Saman], Granger, E.[Eric], Sayed, S.[Saif],
Using deep autoencoders to learn robust domain-invariant representations for still-to-video face recognition,
AVSS17(1-6)
IEEE DOI 1806
Video capture for recognition, high res still for the model. face recognition, feature extraction, image matching, image representation, learning (artificial intelligence), Training BibRef

Sohn, K., Liu, S., Zhong, G., Yu, X., Yang, M.H., Chandraker, M.,
Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos,
ICCV17(5917-5925)
IEEE DOI 1802
face recognition, feature extraction, image matching, image restoration, learning (artificial intelligence), Videos BibRef

Yang, J., Ren, P., Zhang, D., Chen, D., Wen, F., Li, H., Hua, G.,
Neural Aggregation Network for Video Face Recognition,
CVPR17(5216-5225)
IEEE DOI 1711
Face, Face recognition, Feature extraction, Image recognition, Recurrent, neural, networks BibRef

Sawatzky, J., Srikantha, A., Gall, J.,
Weakly Supervised Affordance Detection,
CVPR17(5197-5206)
IEEE DOI 1711
Image segmentation, Robots, Semantics, Supervised learning, Visualization BibRef

Martínez-Díaz, Y.[Yoanna], Hernández, N.[Noslen], Biscay, R.J.[Rolando J.], Chang, L.[Leonardo], Méndez-Vázquez, H.[Heydi], Sucar, L.E.[L. Enrique],
On Fisher vector encoding of binary features for video face recognition,
JVCIR(51), 2018, pp. 155-161.
Elsevier DOI 1802
BibRef
Earlier: A1, A4, A2, A5, A6, Only:
Efficient video face recognition by using Fisher Vector encoding of binary features,
ICPR16(1436-1441)
IEEE DOI 1705
Fisher vector, Binary features, Video. Encoding, Face, Face recognition, Feature extraction, Measurement, Real-time systems, Streaming, media BibRef

Liu, X.P.[Xiu-Ping], Shen, A.H.[Ai-Hong], Zhang, J.[Jie], Cao, J.J.[Jun-Jie], Zhou, Y.F.[Yan-Fang],
Consistent Sparse Representation for Video-Based Face Recognition,
ACCV16(III: 404-418).
Springer DOI 1704
BibRef

Nguyen, D.L.[Dinh-Luan], Tran, M.T.[Minh-Triet],
VFSC: A Very Fast Sparse Clustering to Cluster Faces from Videos,
WFI16(II: 417-433).
Springer DOI 1704
BibRef

Kim, S.T., Kim, D.H., Ro, Y.M.,
Spatio-temporal representation for face authentication by using multi-task learning with human attributes,
ICIP16(2996-3000)
IEEE DOI 1610
Authentication BibRef

Hatimi, H., Fakir, M., Chabi, M.,
Face Recognition Using a Fuzzy Approach and a Multi-agent System from Video Sequences,
CGiV16(442-447)
IEEE DOI 1608
face recognition BibRef

Vinith, B., Akhila, M.K., Naik, N.[Narmada], Rathna, G.N.,
GPU Accelerated Face Recognition System with Enhanced Local Ternary Patterns Using OpenCL,
DICTA15(1-7)
IEEE DOI 1603
face recognition. Incomplete Names in original listing. BibRef

Dornaika, F.[Fadi], Dhabi, R., Ruichek, Y., Bosaghzadeh, A.[Alireza],
Recognizing multiple observations using adaptive graph based label propagation,
IPRIA17(200-205)
IEEE DOI 1712
graph theory, image coding, image recognition, learning (artificial intelligence), semi-supervised learning BibRef

Raducanu, B.[Bogdan], Bosaghzadeh, A.[Alireza], Dornaika, F.[Fadi],
Multi-observation face recognition in videos based on label propagation,
AMFG15(10-17)
IEEE DOI 1510
Databases BibRef

Khan, N.M., Nan, X.M.[Xiao-Ming], Quddus, A., Rosales, E., Guan, L.[Ling],
On video based face recognition through adaptive sparse dictionary,
FG15(1-6)
IEEE DOI 1508
Bayes methods BibRef

Hassanpour, N.[Negar], Chen, L.[Liang],
A hierarchical training and identification method using Gaussian process models for face recognition in videos,
FG15(1-8)
IEEE DOI 1508
Gaussian processes BibRef

Tang, Z.Q.[Zhi-Qiang], Zhang, Y.F.[Yi-Fan], Qiu, S.[Shuang], Lu, H.Q.[Han-Qing],
Video face naming using global sequence alignment,
ICIP14(353-357)
IEEE DOI 1502
Clustering algorithms BibRef

De-la-Torre, M.[Miguel], Granger, E.[Eric], Radtke, P.[Paulo], Sabourin, R.[Robert], Gorodnichy, D.O.[Dmitry O.],
Self-Updating with Facial Trajectories for Video-to-Video Face Recognition,
ICPR14(1669-1674)
IEEE DOI 1412
Adaptation models BibRef

Franco, A.[Annalisa], Maio, D.[Dario], Turroni, F.,
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ICPR14(489-494)
IEEE DOI 1412
Accuracy BibRef

Bendale, A.[Abhijit], Boult, T.E.[Terrance E.],
Towards Open Set Deep Networks,
CVPR16(1563-1572)
IEEE DOI 1612
BibRef
And:
What Do You Do When You Know That You Don't Know?,
Biometrics16(69-76)
IEEE DOI 1612
BibRef
Earlier:
Towards Open World Recognition,
CVPR15(1893-1902)
IEEE DOI 1510
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Bendale, A.[Abhijit], Boult, T.E.[Terrance E.],
Reliable Posterior Probability Estimation for Streaming Face Recognition,
Biometrics14(56-63)
IEEE DOI 1409
SVM; face recognition; incremental learning; probability calibration BibRef

Mishra, R., Kumar, P., Chaudhury, S., Indu, S.,
Monitoring a large surveillance space through distributed face matching,
NCVPRIPG13(1-5)
IEEE DOI 1408
cameras BibRef

Nguyen, H.A.B.[Hoang Anh B.], Li, W.[Wen],
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ICIP13(3715-3719)
IEEE DOI 1402
Face recognition;video representation BibRef

Bolkart, T., Wuhrer, S.,
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3DV13(103-110)
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face recognition BibRef

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Face Recognition in Movie Trailers via Mean Sequence Sparse Representation-Based Classification,
CVPR13(3531-3538)
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l1-minimization BibRef

Wolf, L.B.[Lior B.], Levy, N.[Noga],
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CVPR13(3523-3530)
IEEE DOI 1309
face recognition; pose estimation; similarity score; video; youtube faces BibRef

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Wibowo, M.E., Tjondrongoro, D.[Dian], Zhang, L.G.[Li-Gang], Himawan, I.,
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See also Facial Expression Recognition Using Facial Movement Features. BibRef

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Bredin, H.[Hervé], Poignant, J.[Johann], Tapaswi, M.[Makarand], Fortier, G.[Guillaume], Le, V.B.[Viet Bac], Napoleon, T.[Thibault], Gao, H.[Hua], Barras, C.[Claude], Rosset, S.[Sophie], Besacier, L.[Laurent], Verbeek, J.[Jacob], Quenot, G.[Georges], Jurie, F.[Frederic], Ekenel, H.K.[Hazim Kemal],
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Kan, M.[Meina], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
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Zhang, J.[Jie], Kan, M.[Meina], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
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Earlier:
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ICCV15(3801-3809)
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Zhang, J.[Jie], Kan, M.[Meina], Shan, S.G.[Shi-Guang], Zhao, X.W.[Xiao-Wei], Chen, X.L.[Xi-Lin],
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Springer DOI 1011
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Earlier:
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Liu, X.M.[Xiao-Ming], Chen, T.H.[Tsu-Han],
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Liu, X.M.[Xiao-Ming], Chen, T.H.[Tsu-Han],
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Earlier:
Online Modeling and Tracking of Pose-Varying Faces in Video,
CVPR05(II: 1189).
IEEE DOI 0507
BibRef
Earlier:
Video-Based Face Recognition Using Adaptive Hidden Markov Models,
CVPR03(I: 340-345).
IEEE DOI 0307

See also Video-Based Face Model Fitting Using Adaptive Active Appearance Model. BibRef

Gross, R.[Ralph], Brajovic, V.[Vladimir],
An Image Preprocessing Algorithm for Illumination Invariant Face Recognition,
AVBPA03(10-18).
Springer DOI 0310
BibRef

Gross, R.[Ralph], Yang, J.[Jie], Waibel, A.[Alex],
Growing Gaussian Mixture Models for Pose Invariant Face Recognition,
ICPR00(Vol I: 1088-1091).
IEEE DOI 0009
BibRef

Shakhnarovich, G.[Gregory], Fisher, J.W.[John W.], Darrell, T.J.[Trevor J.],
Face Recognition from Long-Term Observations,
ECCV02(III: 851 ff.).
Springer DOI 0205
Include Gait:
See also Integrated Face and Gait Recognition from Multiple Views. BibRef

Shakhnarovich, G., Viola, P.A., Moghaddam, B.,
A unified learning framework for real time face detection and classification,
AFGR02(14-21).
IEEE DOI 0206
BibRef

Li, Y.,
Video-based online face recognition using identity surfaces,
RATFG01(xx-yy). 0106
BibRef

Weng, J.Y.[Ju-Yang], Evans, C.H.[Colin H.], Hwang, W.S.[Wey-Shiuan],
An Incremental Learning Method for Face Recognition under Continuous Video Stream,
AFGR00(251-256).
IEEE DOI 0003
BibRef
Earlier:
Automated Animal-like Learning for Developing a Face Recognition System,
AVBPA99(xx-yy). BibRef

Ho, P.[Purdy],
Rotation Invariant Real-time Face Detection and Recognition System,
MIT AIM-2001-010, May 31, 2001.
WWW Link. 0205
BibRef

Yamaguchi, O.[Osamu], Fukui, K.[Kazuhiro], Maeda, K.,
Face Recognition Using Temporal Image Sequence,
AFGR98(318-323).
IEEE DOI BibRef 9800

Nagao, K.[Kenji], Sohma, M.[Masaki],
Weak Orthogonalization of Face and Perturbation for Recognition,
CVPR98(845-852).
IEEE DOI BibRef 9800

Nagao, K., Sohma, M.,
Recognizing faces by weakly orthogonalizing against perturbations,
ECCV98(II: 613).
Springer DOI BibRef 9800

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Face Recognition from Video, Faces in Video, Chellappa Group Papers .


Last update:Nov 26, 2024 at 16:40:19