18.3.4.2 Background Detection, Background Model

Mukawa, N., Kuroda, H.,
Uncovered Background Prediction in Interframe Coding,
Commun(33), 1985, pp. 1227-1231. See also Interframe Coding System for Video Teleconferencing Signal Transmission at a 1.5 Mbit/S Rate, An. BibRef 8500

Morton, R.R.A.[Roger R. A.], Lewis, S.[Scott],
Forward look ahead techniques for tracking background and noise levels in scanned video images,
US_Patent4,853,795, Aug 1, 1989
WWW Version. BibRef 8908

Long, W., Yang, Y.H.,
Stationary Background Generation: An Alternative to the Difference of Two Images,
PR(23), No. 12, 1990, pp. 1351-1359.
WWW Version. BibRef 9000

Yang, Y.H., Levine, M.D.,
The Background Primal Sketch: An Approach for Tracking Moving Objects,
MVA(5), 1992, pp. 17-34. BibRef 9200

Lettera, C., Masera, L.,
Foreground/background segmentation in videotelephony,
SP:IC(1), No. 2, October 1990, pp. 181-189.
WWW Version. 0001
BibRef

Thoma, R.[Robert], Bierling, M.[Matthias],
Motion compensating interpolation considering covered and uncovered background,
SP:IC(1), No. 2, October 1990, pp. 191-212.
WWW Version. 0001
Motion compensating interpolation; digital television sequences; low bit rate codec; hierarchical blockmatching; change detection; segmentation BibRef

Elnagar, A., Basu, A.,
Motion Detection Using Background Constraints,
PR(28), No. 10, October 1995, pp. 1537-1554.
WWW Version. BibRef 9510

Neri, A., Colonnese, S., Russo, G., Talone, P.,
Automatic Moving Object and Background Separation,
SP(66), No. 2, April 1998, pp. 219-232. 9807
BibRef

Khosravi, M.[Mehdi], Moed, M.C.[Michael C.], Crabtree, R.N.[Ralph N.], Perez-Jacome, J.E.[Jorge E.],
System and method for multi-resolution background adaptation,
US_Patent6,061,088, May 9, 2000
WWW Version. BibRef 0005

Crabtree, R.N.[Ralph N.], Moed, M.C.[Michael C.], Khosravi, M.[Mehdi],
System and method for matching image information to object model information,
US_Patent6,185,314, Feb 6, 2001
WWW Version. BibRef 0102
And:
System and method for tracking movement of objects in a scene using correspondence graphs,
US_Patent6,295,367, Sep 25, 2001
WWW Version. BibRef

Sullivan, J., Blake, A., Isard, M., MacCormick, J.P.,
Bayesian Object Localisation in Images,
IJCV(44), No. 2, September 2001, pp. 111-135.
WWW Version. 0110
BibRef
Earlier:
Object Localization by Bayesian Correlation,
ICCV99(1068-1075).
IEEE DOI Link Model both foreground (the object) and the background. Apply a bank of (approximately) independent filters, learn background/foreground distributions. BibRef

Sullivan, J., Blake, A., Rittscher, J.,
Statistical Foreground Modelling for Object Localisation,
ECCV00(II: 307-323).
WWW Version. 0003
BibRef

Danielsson, O.[Oscar], Carlsson, S.[Stefan],
Generic Object Class Detection Using Feature Maps,
SCIA11(348-359).
Springer DOI Link 1105
BibRef
Earlier:
Generic Object Class Detection Using Boosted Configurations of Oriented Edges,
ACCV10(II: 1-14).
Springer DOI Link 1011
BibRef

Danielsson, O.[Oscar], Carlsson, S.[Stefan], Sullivan, J.[Josephine],
Automatic learning and extraction of multi-local features,
ICCV09(917-924).
IEEE DOI Link 0909
BibRef
Earlier:
Object Detection Using Multi-local Feature Manifolds,
DICTA08(612-618).
IEEE DOI Link 0812
Each feature a collection of local features. BibRef

Rittscher, J., Kato, J., Joga, S., Blake, A.,
A Probabilistic Background Model for Tracking,
ECCV00(II: 336-350).
WWW Version. 0003
BibRef

Durucan, E., Ebrahimi, T.,
Change detection and background extraction by linear algebra,
PIEEE(89), No. 10, October 2001, pp. 1368-1381.
IEEE DOI Link BibRef 0110

Durucan, E., Ebrahimi, T.,
Moving object detection between multiple and color images,
AVSBS03(243-251).
IEEE Abstract. 0310
BibRef

Durucan, E., Snoeckx, J., Weilenmann, Y.,
Illumination invariant background extraction,
CIAP99(1136-1139).
IEEE DOI Link 9909
BibRef

Cavallaro, A., and Ebrahimi, T.,
Accurate video object segmentation through change detection,
ICME02(I: 445-448). BibRef 0200

Ren, Y.[Ying], Chua, C.S.[Chin-Seng], Ho, Y.K.[Yeong-Khing],
Statistical background modeling for non-stationary camera,
PRL(24), No. 1-3, January 2003, pp. 183-196.
Elsevier DOI Link 0211
BibRef

Herrero-Jaraba, E.[Elías], Orrite-Uruñuela, C.[Carlos], Senar, J.[Jesús],
Detected motion classification with a double-background and a Neighborhood-based difference,
PRL(24), No. 12, August 2003, pp. 2079-2092.
WWW Version. 0304
BibRef

Lipton, A.J.[Alan J.], Allmen, M.C.[Mark C.], Haering, N.C.[Niels C.], Severson, W.[William], Strat, T.M.[Thomas M.],
Video segmentation using statistical pixel modeling,
US_Patent6,625,310, Sep 23, 2003
WWW Version. BibRef 0309
And: US_Patent7,224,852, May 29, 2007
WWW Version. Foreground and background detection. BibRef

Lipton, A.J.[Alan J.], Haering, N.C.[Niels C.], Allmen, M.C.[Mark C.], Venetianer, P.L.[Peter L.], Slowe, T.E.[Thomas E.], Zhang, Z.[Zhong],
Video scene background maintenance using statistical pixel modeling,
US_Patent6,987,883, Jan 17, 2006
WWW Version. BibRef 0601

Cho, J.H.[Ju-Hyun], Kim, S.D.[Seong-Dae],
Object detection using multi-resolution mosaic in image sequences,
SP:IC(20), No. 3, March 2005, pp. 233-253.
WWW Version. 0501
BibRef

Lee, C.N.[Cheoung N.], Samaddar, S.[Sumitro],
Background recovery in monocular vision,
US_Patent5,684,887, Nov 4, 1997
WWW Version. BibRef 9711

Chang, G.H.[Gyu-Hwan], Jung, H.M.[Hae-Mook], Kim, S.D.[Seong-Dae], Choi, J.G.[Jae-Gark], Lee, S.W.[Si-Woong], Cho, S.J.[Soon-Jae],
Method for segmenting and estimating a moving object motion using a hierarchy of motion models,
US_Patent5,734,737, Mar 31, 1998
WWW Version. Frame difference, region segmentation. BibRef 9803

Cooper, F.J.[Frederick J.], Skarbo, R.A.[Rune A.],
Method of presence detection using video input,
US_Patent5,892,856, Apr 6, 1999
WWW Version. BibRef 9904

Mertens, M.J.W.[Mark Jozef Willem], de Haan, G.[Gerard],
Foreground/background detector,
US_Patent6,771,799, Aug 3, 2004
WWW Version. BibRef 0408

Hillman, P., Hannah, J., Renshaw, D.,
Semi-automatic foreground/background segmentation of motion picture images and image sequences,
VISP(152), No. 4, August 2005, pp. 387-397.
WWW Version. 0512
BibRef
Earlier:
Alpha Channel Estimation in High Resolution Images and Image Sequences,
CVPR01(I:1063-1068).
IEEE Abstract. 0110
Segment actor from background. BibRef

Butler, D.E.[Darren E.], Bove, Jr., V.M.[V. Michael], Sridharan, S.[Sridha],
Real-Time Adaptive Foreground/Background Segmentation,
JASP(2005), No. 14, 2005, pp. 2292-2304.
WWW Version. 0603
BibRef

Pless, R.[Robert],
Spatio-temporal Background Models for Outdoor Surveillance,
JASP(2005), No. 14, 2005, pp. 2281-2291.
WWW Version.
PDF Version. 0603
BibRef

Pless, R., Larson, J., Siebers, S., Westover, B.,
Evaluation of local models of dynamic backgrounds,
CVPR03(II: 73-78).
IEEE Abstract. 0307
BibRef

Kolmogorov, V.[Vladimir], Criminisi, A.[Antonio], Blake, A.[Andrew], Cross, G.[Geoffrey], Rother, C.[Carsten],
Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation,
IJCV(76), No. 2, February 2008, pp. 107.
Springer DOI Link 0801
Part of the CVPR 2005 Award Issue. BibRef
And: PAMI(28), No. 9, September 2006, pp. 1480-1492.
IEEE DOI Link 0608
BibRef
Earlier: CVPR05(II: 407-414).
IEEE DOI Link 0507
Award, CVPR. BibRef
And:
Bi-Layer Segmentation of Binocular Stereo Video,
CVPR05(II: 1186).
IEEE DOI Link 0507
Award, CVPR, HM. Real-time segmentation of foreground/background in stereo video. Two different sets, fuse stereo match with color to get layers, fuse color with stereo hypotheses. BibRef

Wang, Y.[Yi],
Implementation of Bilayer Segmentation of Live Video,
OnlineCaltech 2006.
WWW Version. Code, Motion Segmentation. See also Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation. BibRef 0600

Grundmann, M.[Matthias], Kwatra, V.[Vivek], Han, M.[Mei], Essa, I.A.[Irfan A.],
Efficient hierarchical graph-based video segmentation,
CVPR10(2141-2148).
IEEE DOI Link 1006
BibRef

Yin, P.[Pei], Criminisi, A.[Antonio], Winn, J.[John], Essa, I.A.[Irfan A.],
Bilayer Segmentation of Webcam Videos Using Tree-Based Classifiers,
PAMI(33), No. 1, January 2011, pp. 30-42.
IEEE DOI Link 1011
BibRef
Earlier:
Tree-based Classifiers for Bilayer Video Segmentation,
CVPR07(1-8).
IEEE DOI Link 0706
Automatic segmentation for video, monocular camera, approximate depth segmentation form stereo. Frames into foreground/background layers. BibRef

Criminisi, A., Cross, G., Blake, A., Kolmogorov, V.[Vladimir],
Bilayer Segmentation of Live Video,
CVPR06(I: 53-60).
IEEE DOI Link 0606
BibRef

Colombari, A.[Andrea], Fusiello, A.[Andrea], Murino, V.[Vittorio],
Segmentation and tracking of multiple video objects,
PR(40), No. 4, April 2007, pp. 1307-1317.
WWW Version. 0701
BibRef
And:
Video Objects Segmentation by Robust Background Modeling,
CIAP07(155-164).
IEEE DOI Link 0709
BibRef
Earlier:
Background Initialization in Cluttered Sequences,
PercOrg06(197).
IEEE DOI Link 0609
Content-based representation; MPEG; Video coding; Video sequence analysis; Mosaicing; Motion segmentation BibRef

Colombari, A.[Andrea], Cristani, M.[Marco], Murino, V.[Vittorio], Fusiello, A.[Andrea],
Exemplar-based background model initialization,
VSSN05(29-36).
WWW Version. 0511
BibRef

Colombari, A.[Andrea], Fusiello, A.[Andrea],
Patch-Based Background Initialization in Heavily Cluttered Video,
IP(19), No. 4, April 2010, pp. 926-933.
IEEE DOI Link 1003
BibRef

Yalcin, H.[Hulya], Collins, R.[Robert], Hebert, M.[Martial],
Background Estimation under Rapid Gain Change in Thermal Imagery,
CVIU(106), No. 2-3, May-June 2007, pp. 148-161.
WWW Version. 0705
BibRef
Earlier: OTCBVS05(III: 12-12).
IEEE DOI Link 0507
Automatic gain control; Thermal sensors; Airborne video imagery Moving ground vehicles. BibRef

Nanda, P.K.[Pradipta Kumar], Ghosh, A.[Asish], Kanungo, P.[Priyadarshi],
Classification of Objects and Background Using Parallel Genetic Algorithm Based Clustering,
ELCVIA(6), No. 3, 2007, pp. 42-53.
WWW Version. 0803
BibRef

Wang, W.Q.A.[Wei-Qi-Ang], Yang, J.[Jie], Gao, W.[Wen],
Modeling Background and Segmenting Moving Objects from Compressed Video,
CirSysVideo(18), No. 5, May 2008, pp. 670-681.
IEEE DOI Link 0711
BibRef

Wang, W.Q.A.[Wei-Qi-Ang], Chen, D.T.[Da-Tong], Gao, W.[Wen], Yang, J.[Jie],
Modeling background from compressed video,
PETS05(161-168).
IEEE DOI Link 0602
BibRef

Zhang, X.[Xiang], Yang, J.[Jie],
Moving object detection based on shape prediction,
JOSA-A(26), No. 2, February 2009, pp. 342-349.
WWW Version. 0902
BibRef

Ren, Y.[Ying], Chua, C.S.[Chin Seng], Ho, Y.K.[Yeong Khing],
Motion Detection From Time-varied Background,
IJIG(2), No. 2, April 2002, pp. 163-178. 0204
BibRef

Buehler, C.J.[Christopher J.],
Method and apparatus for computerized image background analysis,
US_Patent7,221,775, May 22, 2007
WWW Version. BibRef 0705
And:
Method of counting objects in a monitored environment and apparatus for the same,
US_Patent7,346,187, Mar 18, 2008
WWW Version. BibRef
And: US_Patent7,394,852, Jul 1, 2008
WWW Version. BibRef

Jiang, H.[Hongtu], Owall, V., Ardo, H.[Hakan],
A Hardware Architecture for Real-Time Video Segmentation Utilizing Memory Reduction Techniques,
CirSysVideo(19), No. 2, February 2009, pp. 226-236.
IEEE DOI Link 0902
BibRef
Earlier: A1, A3, A2:
Real-Time Video Segmentation with VGA Resolution and Memory Bandwidth Reduction,
AVSBS06(104-104).
IEEE DOI Link 0611
BibRef

Kristensen, F.[Fredrik], Nilsson, P.[Peter], Öwall, V.[Viktor],
Background Segmentation Beyond RGB,
ACCV06(II:602-612).
Springer DOI Link 0601
BibRef

Tavakkoli, A.[Alireza], Nicolescu, M.[Mircea], Bebis, G.N.[George N.], Nicolescu, M.[Monica],
Non-parametric statistical background modeling for efficient foreground region detection,
MVA(20), No. 6, October 2009, pp. xx-yy.
Springer DOI Link 0910
BibRef
Earlier:
Efficient background modeling through incremental Support Vector Data Description,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Tavakkoli, A.[Alireza], Ambardekar, A.[Amol], Nicolescu, M.[Mircea], Louis, S.[Sushil],
A Genetic Approach to Training Support Vector Data Descriptors for Background Modeling in Video Data,
ISVC07(II: 318-327).
Springer DOI Link 0711
BibRef

Tavakkoli, A.[Alireza], Nicolescu, M.[Mircea], Bebis, G.N.[George N.],
A Novelty Detection Approach for Foreground Region Detection in Videos with Quasi-stationary Backgrounds,
ISVC06(I: 40-49).
Springer DOI Link 0611
BibRef
And:
Automatic Statistical Object Detection for Visual Surveillance,
Southwest06(144-148).
IEEE DOI Link 0603
BibRef
And:
Robust Recursive Learning for Foreground Region Detection in Videos with Quasi-Stationary Backgrounds,
ICPR06(I: 315-318).
IEEE DOI Link 0609
BibRef
Earlier:
Automatic Robust Background Modeling Using Multivariate Non-parametric Kernel Density Estimation for Visual Surveillance,
ISVC05(363-370).
Springer DOI Link 0512
BibRef

El Baf, F.[Fida], and Bouwmans, T.[Thierry],
Robust fuzzy statistical modeling of dynamic backgrounds in IR videos,
SPIE(Newsroom), November 13, 2009.
WWW Version. 0911
Taking into account uncertainties in classification results in an improved alternative to conventional means of detecting moving objects. BibRef

El Baf, F.[Fida], Bouwmans, T.[Thierry], Vachon, B.[Bertrand],
Fuzzy statistical modeling of dynamic backgrounds for moving object detection in infrared videos,
OTCBVS09(60-65).
IEEE DOI Link 0906
BibRef
Earlier:
Type-2 Fuzzy Mixture of Gaussians Model: Application to Background Modeling,
ISVC08(I: 772-781).
Springer DOI Link 0812
BibRef
And:
Fuzzy foreground detection for infrared videos,
OTCBVS08(1-6).
IEEE DOI Link 0806
BibRef
And:
A fuzzy approach for background subtraction,
ICIP08(2648-2651).
IEEE DOI Link 0810
BibRef

Kwak, S.[Sooyeong], Bae, G.[Guntae], Byun, H.[Hyeran],
Moving-object segmentation using a foreground history map,
JOSA-A(27), No. 2, February 2010, pp. 180-187.
WWW Version. 1002
BibRef

Chiu, C.C., Ku, M.Y., Liang, L.W.,
A Robust Object Segmentation System Using a Probability-Based Background Extraction Algorithm,
CirSysVideo(20), No. 4, April 2010, pp. 518-528.
IEEE DOI Link 1003
BibRef

Hyun, M.H.[Myung-Han], Kim, S.Y.[Sung-Yeol], Kang, Y.S.[Yun-Suk], Ho, Y.S.[Yo-Sung],
Multiview foreground extraction and composition to multiview background using trimap sharing for natural 3D scene generation,
IJIST(20), No. 3, September 2010, pp. 285-293.
WWW Version. 1008
BibRef

Tzevanidis, K.[Konstantinos], Argyros, A.[Antonis],
Unsupervised learning of background modeling parameters in multicamera systems,
CVIU(115), No. 1, January 2011, pp. 105-116.
Elsevier DOI Link
WWW Version. 1011
Background modeling; Foreground detection; Multicamera consensus; Particle Swarm Optimization; Camera networks BibRef

Reddy, V.[Vikas], Sanderson, C.[Conrad], Lovell, B.C.[Brian C.],
A Low-Complexity Algorithm for Static Background Estimation from Cluttered Image Sequences in Surveillance Contexts,
JIVP(2011), No. 2011, pp. xx-yy.
WWW Version. 1101
BibRef
Earlier:
Robust Foreground Object Segmentation via Adaptive Region-Based Background Modelling,
ICPR10(3939-3942).
IEEE DOI Link 1008
BibRef

Reddy, V.[Vikas], Sanderson, C.[Conrad], Sanin, A.[Andres], Lovell, B.C.[Brian C.],
MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos,
ACCV10(III: 547-559).
Springer DOI Link 1011
BibRef
Earlier:
Adaptive Patch-Based Background Modelling for Improved Foreground Object Segmentation and Tracking,
AVSS10(172-179).
IEEE DOI Link 1009
BibRef

Valentine, B.[Brian], Apewokin, S.[Senyo], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott],
An efficient, chromatic clustering-based background model for embedded vision platforms,
CVIU(114), No. 11, November 2010, pp. 1152-1163.
Elsevier DOI Link
WWW Version. 1011
Background modeling; Multimodal; Computer vision; Embedded computing BibRef

Valentine, B.[Brian], Choi, J.[Jee], Apewokin, S.[Senyo], Wills, L.M.[Linda M.], Wills, J.S.[J. Scott],
Bypassing BigBackground: An efficient hybrid background modeling algorithm for embedded video surveillance,
ICDSC08(1-8).
IEEE DOI Link 0809
BibRef

Valentine, B.[Brian], Apewokin, S.[Senyo], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott], Gentile, A.,
Midground object detection in real world video scenes,
AVSBS07(517-522).
IEEE DOI Link 0709
BibRef
And: A2, A1, A3, A4, A5:
Multimodal Mean Adaptive Backgrounding for Embedded Real-Time Video Surveillance,
EmbedCV07(1-6).
IEEE DOI Link 0706
BibRef

Bales, M.R.[M. Ryan], Forsthoefel, D.[Dana], Valentine, B.[Brian], Wills, D.S.[D. Scott], Wills, L.M.[Linda M.],
BigBackground-Based Illumination Compensation for Surveillance Video,
JIVP(2011), No. 2011, pp. xx-yy.
WWW Version. 1101
BibRef
And: A1, A2, A4, A5, Only:
Illumination change compensation techniques to improve kinematic tracking,
WACV11(434-439).
IEEE DOI Link 1101
BibRef
Earlier: A1, A2, A4, A5, Only:
Chromatic Sensitivity of Illumination Change Compensation Techniques,
ISVC10(I: 211-220).
Springer DOI Link 1011
BibRef

Yamamoto, A.[Ayaka], Iwai, Y.[Yoshio], Ishiguro, H.[Hiroshi],
Real-Time Object Detection Using Adaptive Background Model and Margined Sign Correlation,
IEICE(E94-D), No. 2, February 2011, pp. 325-335.
WWW Version. 1102
BibRef
Earlier: A1, A2, Only:
Real-Time Object Detection with Adaptive Background Model and Margined Sign Correlation,
ACCV09(III: 65-74).
Springer DOI Link 0909
BibRef

Yoshimura, H.[Hironori], Iwai, Y.[Yoshio], Yachida, M.[Masahiko],
Object Detection with Adaptive Background Model and Margined Sign Cross Correlation,
ICPR06(III: 19-23).
IEEE DOI Link 0609
BibRef

Evangelio, R.H.[Rubén Heras], Sikora, T.[Thomas],
Static Object Detection Based on a Dual Background Model and a Finite-State Machine,
JIVP(2011), No. 2011, pp. xx-yy.
WWW Version. 1103
See also system for automatic and interactive detection of static objects, A. BibRef

Evangelio, R.H.[Rubén Heras], Sikora, T.[Thomas],
Complementary background models for the detection of static and moving objects in crowded environments,
AVSBS11(71-76).
IEEE DOI Link 1111
BibRef

Suhr, J.K., Jung, H.G., Li, G., Noh, S.I., Kim, J.,
Background Compensation for Pan-Tilt-Zoom Cameras Using 1-D Feature Matching and Outlier Rejection,
CirSysVideo(21), No. 3, March 2011, pp. 371-377.
IEEE DOI Link 1104
BibRef

Lopez-Rubio, E.[Ezequiel], Luque-Baena, R.M.[Rafael Marcos],
Stochastic approximation for background modelling,
CVIU(115), No. 6, June 2011, pp. 735-749.
Elsevier DOI Link
WWW Version. 1104
Background modelling; Probabilistic mixture models; Stochastic approximation; Unsupervised learning BibRef

Lee, W.W.[Won-Woo], Woo, W.T.[Woon-Tack], Boyer, E.[Edmond],
Silhouette Segmentation in Multiple Views,
PAMI(33), No. 7, July 2011, pp. 1429-1441.
IEEE DOI Link 1106
BibRef
Earlier:
Identifying Foreground from Multiple Images,
ACCV07(II: 580-589).
Springer DOI Link 0711
Consistent foreground regions. Exploit spatial consistency of several projections. BibRef

Kirchhof, M.[Michael], Stilla, U.[Uwe],
Statistical Unbiased Background Modeling for Moving Platforms,
PIA11(245-256).
Springer DOI Link 1110
BibRef

Li, D.[Dawei], Xu, L.H.[Li-Hong], Goodman, E.,
Online background learning for illumination-robust foreground detection,
ICARCV10(1093-1100).
IEEE DOI Link 1109
BibRef

Li, P.[Peng], Wang, C.H.[Chen-Hao], Wang, C.J.[Chong-Jing], Liu, Y.C.[Yun-Cai],
Adaptive Background Model for Arbitrary-Long Stationary Target,
ICIG11(558-561).
IEEE DOI Link 1109
BibRef

Quivy, C.H.[Charles-Henri], Kumazawa, I.[Itsuo],
Background Images Generation Based on the Nelder-Mead Simplex Algorithm Using the Eigenbackground Model,
ICIAR11(I: 21-29).
Springer DOI Link 1106
BibRef

Su, T.F.[Te-Feng], Chen, Y.L.[Yi-Ling], Lai, S.H.[Shang-Hong],
Over-Segmentation Based Background Modeling and Foreground Detection with Shadow Removal by Using Hierarchical MRFs,
ACCV10(III: 535-546).
Springer DOI Link 1011
BibRef

Jarraya, S.K.[Salma Kammoun], Hammami, M.[Mohamed], Ben-Abdallah, H.[Hanene],
Accurate Background Modeling for Moving Object Detection in a Dynamic Scene,
DICTA10(52-57).
IEEE DOI Link 1012
BibRef

Paul, M.[Manoranjan], Lin, W.S.[Wei-Si], Lau, C.T.[Chiew Tong], Lee, B.S.[Bu-Sung],
Pattern based video coding with uncovered background,
ICIP10(2065-2068).
IEEE DOI Link 1009
BibRef

Yam, K.Y.[Kin-Yi], Siu, W.C.[Wan-Chi], Law, N.F.[Ngai-Fong], Chan, C.K.[Chok-Ki],
Fast video object detection via multiple background modeling,
ICIP10(729-732).
IEEE DOI Link 1009
BibRef

Cuevas, C.[Carlos], Garcia, N.[Narciso],
Automatic bandwidth estimation strategy for high-quality non-parametric modeling based moving object detection,
ICIP11(1757-1760).
IEEE DOI Link 1201
BibRef
Earlier:
Tracking-based non-parametric background-foreground classification in a chromaticity-gradient space,
ICIP10(845-848).
IEEE DOI Link 1009
BibRef

Huang, T.[Tianci], Qiu, J.B.[Jing-Bang], Sakayori, T.[Takahiro], Ikenaga, T.[Takeshi],
Robust Background Segmentation Using Background Models for Surveillance Application,
MVA09(402-).
PDF Version. 0905
BibRef

Baltieri, D., Vezzani, R., Cucchiara, R.,
Fast Background Initialization with Recursive Hadamard Transform,
AVSS10(165-171).
IEEE DOI Link 1009
BibRef

Scott, J., Pusateri, M.A., Cornish, D.,
Kalman filter based video background estimation,
AIPR09(1-7).
IEEE DOI Link 0910
BibRef

Murshed, M., Ramirez, A., Chae, O.,
Statistical Background Modeling: An Edge Segment Based Moving Object Detection Approach,
AVSS10(300-306).
IEEE DOI Link 1009
BibRef

Kita, Y.[Yasuyo],
Background Modeling by Combining Joint Intensity Histogram with Time-sequential Data,
ICPR10(991-994).
IEEE DOI Link 1008
BibRef

Caseiro, R.[Rui], Henriques, J.F.[Joao F.], Martins, P.[Pedro], Batista, J.P.[Jorge P.],
A nonparametric Riemannian framework on tensor field with application to foreground segmentation,
ICCV11(1-8).
IEEE DOI Link 1201
BibRef

Caseiro, R.[Rui], Henriques, J.F.[Joao F.], Batista, J.P.[Jorge P.],
Foreground Segmentation via Background Modeling on Riemannian Manifolds,
ICPR10(3570-3574).
IEEE DOI Link 1008
See also Globally optimal solution to multi-object tracking with merged measurements. BibRef

Caseiro, R.[Rui], Batista, J.[Jorge], Martins, P.[Pedro],
Background Modelling on Tensor Field for Foreground Segmentation,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Forczmanski, P.[Pawel], Seweryn, M.[Marcin],
Surveillance Video Stream Analysis Using Adaptive Background Model and Object Recognition,
ICCVG10(I: 114-121).
Springer DOI Link 1009
BibRef

Uegaki, H.[Hiroshi], Nakashima, Y.[Yuta], Babaguchi, N.[Noboru],
Discriminating Intended Human Objects in Consumer Videos,
ICPR10(4380-4383).
IEEE DOI Link 1008
BibRef

Nakashima, Y.[Yuta], Babaguchi, N.[Noboru], Fan, J.P.[Jian-Ping],
Detecting intended human objects in human-captured videos,
POCV10(33-40).
IEEE DOI Link 1006
I.e. what the person intended to capture in the video. BibRef

Liu, X.D.[Xue-Dong], Wang, H.[Hong],
A fast motion segmentation algorithm based on hypothesis test for surveillance video coding,
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ICIP09(3201-3204).
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ICIP09(3221-3224).
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ICIP09(3225-3228).
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ICIP09(3241-3244).
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CISP09(1-5).
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AVSBS08(41-48).
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See also Commentary Paper 2 on On Stable Dynamic Background Generation Technique Using Gaussian Mixture Models for Robust Object Detection. See also Commentary Paper 1 on On Stable Dynamic Background Generation Technique Using Gaussian Mixture Models for Robust Object Detection. BibRef

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Harville, M., Gordon, G.G., Woodfill, J.I.,
Adaptive Video Background Modeling Using Color and Depth,
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A Novel Algorithm of Adaptive Background Estimation,
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Derive a 3-D model for the background to use in foreground tracking. BibRef

Stenger, B.[Bjoern], Ramesh, V.[Visvanathan], Paragios, N.[Nikos], Coetzee, F.[Frans], Buhmann, J.M.[Joachim M.],
Topology Free Hidden Markov Models: Application to Background Modeling,
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Gao, X.[Xiang], Boult, T.E., Coetzee, F.[Frans], Ramesh, V.[Visvanathan],
Error Analysis of Background Adaption,
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Qian, R.J.[Richard J.], Sezan, M.I.[M. Ibrahim],
Video Background Replacement Without A Blue Screen,
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Direct Identification of Moving Objects and Background from 2D Motion Models,
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Background Modeling for Segmentation of Video-rate Stereo Sequences,
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Toyama, K., Krumm, J., Brumitt, B., Meyers, B.,
Wallflower: Principles and Practice of Background Maintenance,
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Martins, F.C.M.[Fernando C.M.], Nickerson, B.R.[Brian R.], Bostrom, V.S.[Vareck S.], Hazra, R.[Rajeeb],
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Martins, I., Corte-Real, L.,
A video coder using 3-D model based background for video surveillance applications,
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Hwang, T.L., Clark, J.J.[James J.],
On local detection of moving edges,
ICPR90(I: 180-184).
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Chen, S., Li, Z., Zhang, G.,
A Renovated Algorithm for Extracting Moving Target from Background in Real Time Video Tracking System,
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Chapter on Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Background Models, Textured Surfaces, Regions .