12.1.4.2 Information Fusion, Sensor Fusion

Chapter Contents (Back)
Fusion. Sensor Fusion. Knowledge-Based Vision. See also Decision Fusion.

Desachy, J., Roux, L., Zahzah, E.H.,
Numeric and Symbolic Data Fusion: A Soft Computing Approach to Remote Sensing Images Analysis,
PRL(17), No. 13, November 25 1996, pp. 1361-1378. 9701
Remote Sensing. BibRef

Desachy, J., Zahzah, E.H.,
Symbolic and iconic information combination for satellite imagery interpretation,
CAIP93(335-342).
Springer DOI 9309
BibRef

Bosse, E., Roy, J.,
Fusion of Identity Declarations from Dissimilar Sources Using the Dempster-Shafer Theory,
OptEng(36), No. 3, March 1997, pp. 648-657. 9704
BibRef

Cantoni, V.[Virginio], Setti, A.[Alessandra], di Gesu, V.[Vito], Tegolo, D.[Domenico],
Human and Machine Perception: Information Fusion,
Plenum1997. ISBN 0-306-45708-0. 350 pp. Proceeding of a conference. BibRef 9700

Rao, N.S.V.,
Nadaraya-Watson Estimator for Sensor Fusion,
OptEng(36), No. 3, March 1997, pp. 642-647. 9704
BibRef

Murphy, R.R.,
Dempster-Shafer Theory For Sensor Fusion In Autonomous Mobile Robots,
RA(14), No. 2, April 1998, pp. 197-206. 9804
BibRef

Solaiman, B., Koffi, R.K., Mouchot, M.C., Hillion, A.,
An Information Fusion Method for Multispectral Image Classification Postprocessing,
GeoRS(36), No. 2, March 1998, pp. 395-406.
IEEE Top Reference. 9804
BibRef

Sester, M.[Monika], Anders, K.H.[Karl-Heinrich], Walter, V.[Volker],
Linking Objects of Different Spatial Data Sets by Integration and Aggregation,
GeoInfo(2), No. 4, December 1998, pp. 335-358.
DOI Link BibRef 9812

Lewis, T.[Tristan], Owens, R.A.[Robyn A.], Baddeley, A.J.[Adrian J.],
Averaging feature maps,
PR(32), No. 9, September 1999, pp. 1615-1630.
WWW Link. Radar maps of flight paths, sketches of faces. BibRef 9909

Baddeley, A.J., Molchanov, I.,
Averaging of Random Sets Based on Their Distance Functions,
JMIV(8), No. 1, January 1998, pp. 79-92.
DOI Link 9803
BibRef

McNary, C.[Charles], Reiser, K.[Kurt], Doria, D.M.[David M.], Webster, D.W.[David W.], Chen, Y.[Yang],
Hierarchical information fusion object recognition system and method,
US_Patent5,963,653, Oct 5, 1999
WWW Link. BibRef 9910

Ricchetti, E.[Evaristo],
Multispectral Satellite Image and Ancillary Data Integration for Geological Classification,
PhEngRS(66), No. 4, April 2000, pp. 429. Comparisons of different procedures for geological classification of multispectral imagery demonstrate the improvement in accuracy of results achieved using terrain information from a digital terrain model (DTM). 0004
BibRef

Bendjebbour, A., Delignon, Y., Fouque, L., Samson, V., Pieczynski, W.,
Multisensor image segmentation using Dempster-Shafer fusion in Markov fields context,
GeoRS(39), No. 8, August 2001, pp. 1789-1798.
IEEE Top Reference. 0109
BibRef

Benboudjema, D.[Dalila], Pieczynski, W.[Wojciech],
Unsupervised image segmentation using triplet Markov fields,
CVIU(99), No. 3, September 2005, pp. 476-498.
WWW Link. 0508
HMF models. Pairwise HMF. BibRef

Benboudjema, D.[Dalila], Pieczynski, W.[Wojciech],
Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields,
PAMI(29), No. 8, August 2007, pp. 1367-1378.
IEEE DOI 0707
BibRef

Allagnat, O., Boucher, J.M., He, D.C., Pieczynski, W.[Wojciech],
Hidden Markov fields and unsupervised segmentation of images,
ICPR92(III:96-100).
IEEE DOI 9208
BibRef

Rao, N.S.V.[Nageswara S.V.],
On Fusers that Perform Better than Best Sensor,
PAMI(23), No. 8, August 2001, pp. 904-909.
IEEE DOI 0109
Analyze fusion techniques. Several senesors meet the criteria -- linear combinations, special potential functions, some feedforward networks. BibRef

Kiema, J.B.K.,
Texture analysis and data fusion in the extraction of topographic objects from satellite imagery,
JRS(23), No. 4, February 2002, pp. 767-776. 0202
BibRef

Alkoot, F.M., Kittler, J.V.,
Modified product fusion,
PRL(23), No. 8, June 2002, pp. 957-965.
Elsevier DOI 0204
BibRef

Dempere-Marco, L., Hu, X.P.[Xiao-Peng], MacDonald, S.L.S., Ellis, S.M., Hansell, D.M., Yang, G.Z.[Guang-Zhong],
The use of visual search for knowledge gathering in image decision support,
MedImg(21), No. 7, July 2002, pp. 741-754.
IEEE Top Reference. 0210
BibRef

Dempere-Marco, L., Hu, X.P., Ellis, S.M., Hansell, D.M., Yang, G.Z.,
Analysis of Visual Search Patterns With EMD Metric in Normalized Anatomical Space,
MedImg(25), No. 8, August 2006, pp. 1011-1021.
IEEE DOI 0608
BibRef

Hu, X.P.[Xiao-Peng], Dempere-Marco, L., Yang, G.Z.[Guang-Zhong],
Hot spot detection based on feature space representation of visual search,
MedImg(22), No. 9, September 2003, pp. 1152-1162.
IEEE Abstract. 0309
BibRef

Hu, X.P.[Xiao-Peng], Dempere-Marco, L.[Laura], Davies, E.R.[E. Roy],
Bayesian feature evaluation for visual saliency estimation,
PR(41), No. 11, November 2008, pp. 3302-3312.
WWW Link. 0808
Object recognition; Bayesian modeling; Visual attention; Visual search; Visual cue selection BibRef

Yang, G.Z.[Guang-Zhong], Dempere-Marco, L.[Laura], Hu, X.P.[Xiao-Peng], Rowe, A.[Anthony],
Visual search: psychophysical models and practical applications,
IVC(20), No. 4, April 2002, pp. 291-305.
WWW Link. 0203
Model Human eye movements. Eye tracking. BibRef

Yang, J.[Jian], Yang, J.Y.[Jing-Yu], Zhang, D.[David], Lu, J.F.[Jian-Feng],
Feature fusion: parallel strategy vs. serial strategy,
PR(36), No. 6, June 2003, pp. 1369-1381.
WWW Link. 0304
Parallel fusion. Handwritten numerals. BibRef

Pontius, Jr., R.G.[R. Gil],
Statistical Methods to Partition Effects of Quantity and Location During Comparison of Categorical Maps at Multiple Resolutions,
PhEngRS(68), No. 10, October 2002, pp. 10411050. Separate five components of agreement between two maps.
WWW Link. 0304
BibRef

Zhu, Y.M.[Yun-Min], Li, X.R.[X. Rong],
Unified fusion rules for multisensor multihypothesis network decision systems,
SMC-A(33), No. 4, July 2003, pp. 502-513.
IEEE Abstract. 0310
BibRef

Rogelj, P.[Peter], Kovacic, S.[Stanislav], Gee, J.C.[James C.],
Point similarity measures for non-rigid registration of multi-modal data,
CVIU(92), No. 1, October 2003, pp. 112-140.
WWW Link. 0310
BibRef

Petrovic, V.S.[Vladimir S.], Xydeas, C.S.[Costas S.],
Gradient-based multiresolution image fusion,
IP(13), No. 2, February 2004, pp. 228-237.
IEEE DOI 0404
BibRef

Xydeas, C.S.[Costas S.], Petrovic, V.S.[Vladimir S.],
Objective image fusion performance measure,
EL(36), No. 4, 2000, pp. 308-309. BibRef 0001

Petrovic, V.S.[Vladimir S.], Xydeas, C.S.[Costas S.],
Objective Image Fusion Performance Characterisation,
ICCV05(II: 1866-1871).
IEEE DOI 0510
BibRef
Earlier:
Evaluation of Image Fusion Performance with Visible Differences,
ECCV04(Vol III: 380-391).
Springer DOI 0405
BibRef

Stepan, P., Kulich, M., Preucil, L.,
Robust data fusion with occupancy grid,
SMC-C(35), No. 1, February 2005, pp. 106-115.
IEEE Abstract. 0501
BibRef

John, S., Vorontsov, M.A.,
Multiframe Selective Information Fusion From Robust Error Estimation Theory,
IP(14), No. 5, May 2005, pp. 577-584.
IEEE DOI 0505
BibRef

Sun, Q.S.[Quan-Sen], Zeng, S.G.[Sheng-Gen], Liu, Y.[Yan], Heng, P.A.[Pheng-Ann], Xia, D.S.[De-Shen],
A new method of feature fusion and its application in image recognition,
PR(38), No. 12, December 2005, pp. 2437-2448.
WWW Link. 0510
canonical correlation analysis. BibRef

Hou, S.D.[Shu-Dong], Sun, Q.S.[Quan-Sen],
An orthogonal regularized CCA learning algorithm for feature fusion,
JVCIR(25), No. 5, 2014, pp. 785-792.
Elsevier DOI 1406
Canonical correlation analysis BibRef

Sun, S., Zhang, C.,
Optimal information fusion distributed smoother for discrete multichannel ARMA signals,
VISP(152), No. 5, October 2005, pp. 583-589.
DOI Link 0512
BibRef

Li, M.[Min], Cai, W.[Wei], Tan, Z.[Zheng],
A region-based multi-sensor image fusion scheme using pulse-coupled neural network,
PRL(27), No. 16, December 2006, pp. 1948-1956.
WWW Link. 0611
Image fusion; Pulse-coupled neural network; Image segmentation BibRef

Parikh, D.[Devi], Polikar, R.[Robi],
An Ensemble-Based Incremental Learning Approach to Data Fusion,
SMC-B(37), No. 2, April 2007, pp. 437-450.
IEEE DOI 0704
BibRef

Zheng, S., Shi, W.Z., Liu, J., Zhu, G.X., Tian, J.W.,
Multisource Image Fusion Method Using Support Value Transform,
IP(16), No. 7, July 2007, pp. 1831-1839.
IEEE DOI 0707
BibRef

Zheng, S., Shi, W.Z., Liu, J., Tian, J.,
Remote Sensing Image Fusion Using Multiscale Mapped LS-SVM,
GeoRS(46), No. 5, May 2008, pp. 1313-1322.
IEEE DOI 0804
BibRef

Zhou, X.[Xiran], Liu, J.[Jun], Liu, S.G.[Shu-Guang], Cao, L.[Lei], Zhou, Q.M.[Qi-Ming], Huang, H.[Huawen],
A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation,
PandRS(88), No. 1, 2014, pp. 16-27.
Elsevier DOI 1402
Image fusion BibRef

Zhang, Y.J.[Ying-Jie],
Adaptive region-based image fusion using energy evaluation model for fusion decision,
SIViP(1), No. 3, August 2007, pp. 215-223.
Springer DOI 0803
BibRef

Bleiholder, J.[Jens], Naumann, F.[Felix],
Data fusion,
Surveys(41), No. 1, December 2008, pp. 1-41.
WWW Link. 0804
Survey, Sensor Fusion. BibRef

Turlapaty, A.C.[Anish C.], Anantharaj, V.G.[Valentine G.], Younan, N.H.[Nicolas H.], Turk, F.J.[F. Joseph],
Precipitation data fusion using vector space transformation and artificial neural networks,
PRL(31), No. 10, 15 July 2010, pp. 1184-1200.
Elsevier DOI 1008
Pattern recognition; Optimization; Data merging; Convergence; Artificial neural networks BibRef

Davenport, M.A., Hegde, C., Duarte, M.F.[Marco F.], Baraniuk, R.G.[Richard G.],
Joint Manifolds for Data Fusion,
IP(19), No. 10, October 2010, pp. 2580-2594.
IEEE DOI 1003
BibRef

Tseng, C.H.[Chien-Hao], Jwo, D.J.[Dah-Jing],
Designing Fuzzy Adaptive Nonlinear Filter for Land Vehicle Ultra-Tightly Coupled Integrated Navigation Sensor Fusion,
Sensors(128), Issue 5, May 2011, pp. 1-16.
HTML Version. 1106
BibRef

Scheirer, W.J.[Walter J.], Rocha, A.[Anderson], Micheals, R.[Ross], Boult, T.E.[Terrance E.],
Meta-Recognition: The Theory and Practice of Recognition Score Analysis,
PAMI(33), No. 8, August 2011, pp. 1689-1695.
IEEE DOI 1107
BibRef
Earlier:
Robust Fusion: Extreme Value Theory for Recognition Score Normalization,
ECCV10(III: 481-495).
Springer DOI 1009
Perfromance prediction for recognition algorithms. Predict system performance for threshold selection, etc. BibRef

Zhang, Q.A.[Qi-Ang], Wang, L.[Long], Li, H.J.[Hui-Juan], Ma, Z.K.[Zhao-Kun],
Similarity-based multimodality image fusion with shiftable complex directional pyramid,
PRL(32), No. 13, 1 October 2011, pp. 1544-1553.
Elsevier DOI 1109
Multimodality image fusion; Shiftable complex directional pyramid transform; Structural similarity index BibRef

Yeh, Y.R., Lin, T.C., Chung, Y.Y., Wang, Y.C.F.,
A Novel Multiple Kernel Learning Framework for Heterogeneous Feature Fusion and Variable Selection,
MultMed(14), No. 3, 2012, pp. 563-574.
IEEE DOI 1202
BibRef

Hwang, K.S., Chen, Y.J., Wu, C.J.,
Fusion of Multiple Behaviors Using Layered Reinforcement Learning,
SMC-A(42), No. 4, July 2012, pp. 999-1004.
IEEE DOI 1206
BibRef

Jang, J.H.[Jae Ho], Bae, Y.S.[Yoon-Sung], Ra, J.B.[Jong Beom],
Contrast-Enhanced Fusion of Multisensor Images Using Subband-Decomposed Multiscale Retinex,
IP(21), No. 8, August 2012, pp. 3479-3490.
IEEE DOI 1208
BibRef
Earlier:
Multi-Sensor Image Fusion Using Subband Decomposed Multiscale Retinex,
ICIP09(2177-2180).
IEEE DOI 0911
See also Sub-Band Decomposed Multiscale Retinex with Space Varying Gain. BibRef

Jang, J.H., Kim, Y.S., Ra, J.B.,
Image enhancement in multi-resolution multi-sensor fusion,
AVSBS07(289-294).
IEEE DOI 0709
BibRef

Sun, M.[Ming], Priebe, C.E.[Carey E.], Tang, M.[Minh],
Generalized canonical correlation analysis for disparate data fusion,
PRL(34), No. 2, 15 January 2013, pp. 194-200.
Elsevier DOI 1212
Manifold matching; Canonical correlation analysis; Reduced rank regression; Efficiency; Classification BibRef

Wang, X., Kankanhalli, M.S.,
Multimedia Fusion With Mean-Covariance Analysis,
MultMed(15), No. 1, January 2013, pp. 120-128.
IEEE DOI 1212
BibRef

Ozkan, D., Morency, L.P.,
Latent Mixture of Discriminative Experts,
MultMed(15), No. 2, 2013, pp. 326-338.
IEEE DOI 1302
lexical, syntactic structure, part-of-speech, visual and prosody Each modality done separately BibRef

Ma, A.J.H.[Andy Jin-Hua], Yuen, P.C.[Pong C.], Lai, J.H.[Jian-Huang],
Linear Dependency Modeling for Classifier Fusion and Feature Combination,
PAMI(35), No. 5, May 2013, pp. 1135-1148.
IEEE DOI 1304
BibRef

Ma, A.J.H.[Andy J.H.], Yuen, P.C.[Pong C.],
Reduced Analytic Dependency Modeling: Robust Fusion for Visual Recognition,
IJCV(109), No. 3, September 2014, pp. 233-251.
WWW Link. 1408
BibRef
Earlier:
Reduced Analytical Dependency Modeling for Classifier Fusion,
ECCV12(III: 792-805).
Springer DOI 1210
BibRef
Earlier:
Linear dependency modeling for feature fusion,
ICCV11(2041-2048).
IEEE DOI 1201
BibRef

Hassen, R.[Rania], Wang, Z.[Zhou], Salama, M.M.A.[Magdy M.A.],
Image Sharpness Assessment Based on Local Phase Coherence,
IP(22), No. 7, 2013, pp. 2798-2810.
IEEE DOI 1307
BibRef
Earlier:
Multi-sensor image registration based-on local phase coherence,
ICIP09(181-184).
IEEE DOI 0911
blur detection; Fourier transforms; Wavelet transforms BibRef

Hassen, R.[Rania], Wang, Z.[Zhou], Salama, M.M.A.[Magdy M.A.],
Objective Quality Assessment for Multiexposure Multifocus Image Fusion,
IP(24), No. 9, September 2015, pp. 2712-2724.
IEEE DOI 1506
BibRef
Earlier:
A Flexible Framework for Local Phase Coherence Computation,
ICIAR11(I: 40-49).
Springer DOI 1106
BibRef
Earlier:
Multifocus Image Fusion Using Local Phase Coherence Measurement,
ICIAR09(54-63).
Springer DOI 0907
image fusion BibRef

Ma, K.[Kede], Zeng, K.[Kai], Wang, Z.[Zhou],
Perceptual Quality Assessment for Multi-Exposure Image Fusion,
IP(24), No. 11, November 2015, pp. 3345-3356.
IEEE DOI 1509
image enhancement BibRef

Yeganeh, H., Rostami, M., Wang, Z.,
Objective Quality Assessment of Interpolated Natural Images,
IP(24), No. 11, November 2015, pp. 4651-4663.
IEEE DOI 1509
Distortion BibRef

Liu, X.[Xing], Jiang, S.S.[Shou-Shan],
Study on the Applications of Cross-Layer Information Fusion in Target Recognition,
Sensors(153), No. 5, May 2013, pp. 129-136.
HTML Version. 1307
BibRef

Maravall, D.[Darío], de Lope, J.[Javier], Fuentes, J.P.[Juan Pablo],
Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images,
PRL(34), No. 14, 2013, pp. 1719-1724.
Elsevier DOI 1308
Learning automata theory BibRef

Kakarala, R.[Ramakrishna], Hebbalaguppe, R.[Ramya],
A method for fusing a pair of images in the JPEG domain,
RealTimeIP(9), No. 2, June 2014, pp. 347-357.
WWW Link. 1407
BibRef

Sharma, K.K., Sharma, M.[Mohit],
Image fusion based on image decomposition using self-fractional Fourier functions,
SIViP(8), No. 7, October 2014, pp. 1335-1344.
WWW Link. 1410
BibRef

Cao, L.[Liu], Jin, L.X.[Long-Xu], Tao, H.J.[Hong-Jiang], Li, G.N.[Guo-Ning], Zhuang, Z.[Zhuang], Zhang, Y.[Yanfu],
Multi-Focus Image Fusion Based on Spatial Frequency in Discrete Cosine Transform Domain,
SPLetters(22), No. 2, February 2015, pp. 220-224.
IEEE DOI 1410
discrete cosine transforms BibRef

Song, H.Y.[Hai-Yu], Zhang, W.A.[Wen-An], Yu, L.[Li],
Hierarchical Fusion in Clustered Sensor Networks with Asynchronous Local Estimates,
SPLetters(21), No. 12, December 2014, pp. 1506-1510.
IEEE DOI 1410
covariance analysis BibRef

Tsai, P.H.[Pei-Hsuan], Lin, Y.J.[Ying-Jun], Ou, Y.Z.[Yi-Zong], Chu, E.T.H., Liu, J.W.S.,
A Framework for Fusion of Human Sensor and Physical Sensor Data,
SMCS(44), No. 9, September 2014, pp. 1248-1261.
IEEE DOI 1410
alarm systems BibRef

Qin, J.Z.[Jian-Zhao], Yung, N.H.C.[Nelson H.C.],
Feature fusion within local region using localized maximum-margin learning for scene categorization,
PR(45), No. 4, 2012, pp. 1671-1683.
Elsevier DOI 1410
Scene categorization BibRef

Zitnik, M., Zupan, B.,
Data Fusion by Matrix Factorization,
PAMI(37), No. 1, January 2015, pp. 41-53.
IEEE DOI 1412
Approximation methods BibRef

Soganli, A., Ercetin, O., Cetin, M.,
On the Quality and Timeliness of Fusion in a Random Access Sensor Network,
SPLetters(22), No. 9, September 2015, pp. 1259-1263.
IEEE DOI 1503
Markov processes BibRef

Bahrampour, S.[Soheil], Nasrabadi, N.M.[Nasser M.], Ray, A.[Asok], Jenkins, K.W.[Kenneth W.],
Multimodal Task-Driven Dictionary Learning for Image Classification,
IP(25), No. 1, January 2016, pp. 24-38.
IEEE DOI 1601
BibRef
Earlier: A1, A3, A2, A4:
Quality-Based Multimodal Classification Using Tree-Structured Sparsity,
CVPR14(4114-4121)
IEEE DOI 1409
face recognition Information fusion. BibRef

Wang, S.[Sheng], Lu, J.F.[Jian-Feng], Gu, X.[Xingjian], Shen, C.H.[Chun-Hua], Xia, R.[Rui], Yang, J.Y.[Jing-Yu],
Canonical principal angles correlation analysis for two-view data,
JVCIR(35), No. 1, 2016, pp. 209-219.
Elsevier DOI 1602
Canonical correlation analysis. CCA. For fusion. BibRef

Yu, J.G.[Jin-Gang], Gao, C.X.[Chang-Xin], Tian, J.W.[Jin-Wen],
Collaborative multicue fusion using the cross-diffusion process for salient object detection,
JOSA-A(33), No. 3, March 2016, pp. 404-415.
DOI Link 1603
Digital image processing BibRef

Pitts, B., Riggs, S.L., Sarter, N.,
Crossmodal Matching: A Critical but Neglected Step in Multimodal Research,
HMS(46), No. 3, June 2016, pp. 445-450.
IEEE DOI 1605
Equating perceived intensities of stimuli across two sensory modalities. BibRef

Wang, K.[Kaiye], He, R.[Ran], Wang, L.[Liang], Wang, W.[Wei], Tan, T.N.[Tie-Niu],
Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval,
PAMI(38), No. 10, October 2016, pp. 2010-2023.
IEEE DOI 1609
BibRef
Earlier: A1, A2, A4, A3, A5:
Learning Coupled Feature Spaces for Cross-Modal Matching,
ICCV13(2088-2095)
IEEE DOI 1403
BibRef
And: A1, A4, A2, A3, A5:
Multi-modal Subspace Learning with Joint Graph Regularization for Cross-Modal Retrieval,
ACPR13(236-240)
IEEE DOI 1408
Buildings. graph theory BibRef

Li, Q.[Qi], Sun, Z.A.[Zhen-An], He, R.[Ran], Tan, T.N.[Tie-Niu],
Joint Alignment and Clustering via Low-Rank Representation,
ACPR13(591-595)
IEEE DOI 1408
image representation BibRef

Wang, K.[Kaiye], Wang, W.[Wei], Wang, L.[Liang],
Learning unified sparse representations for multi-modal data,
ICIP15(3545-3549)
IEEE DOI 1512
Cross-modal retrieval BibRef

Zu, C.[Chen], Wang, Z.X.[Zheng-Xia], Zhang, D.Q.[Dao-Qiang], Liang, P.P.[Pei-Peng], Shi, Y.H.[Yong-Hong], Shen, D.G.[Ding-Gang], Wu, G.R.[Guo-Rong],
Robust multi-atlas label propagation by deep sparse representation,
PR(63), No. 1, 2017, pp. 511-517.
Elsevier DOI 1612
Hierarchical sparse representation BibRef

Fan, C.T., Wang, Y.K., Huang, C.R.,
Heterogeneous Information Fusion and Visualization for a Large-Scale Intelligent Video Surveillance System,
SMCS(47), No. 4, April 2017, pp. 593-604.
IEEE DOI 1704
Artificial intelligence BibRef


Cavallari, T.[Tommaso], di Stefano, L.[Luigi],
On-Line Large Scale Semantic Fusion,
DeepLearn16(III: 83-99).
Springer DOI 1611
BibRef

Lee, H., Kwon, H., Robinson, R.M., Nothwang, W.D., Marathe, A.M.,
Dynamic belief fusion for object detection,
WACV16(1-9)
IEEE DOI 1606
Bayes methods BibRef

Song, G.L.[Guo-Li], Wang, S.H.[Shu-Hui], Huang, Q.M.[Qing-Ming], Tian, Q.[Qi],
Similarity Gaussian Process Latent Variable Model for Multi-modal Data Analysis,
ICCV15(4050-4058)
IEEE DOI 1602
Analytical models BibRef

Shibata, T.[Takashi], Tanaka, M.[Masayuki], Okutomi, M.[Masatoshi],
Unified image fusion based on application-adaptive importance measure,
ICIP15(1-5)
IEEE DOI 1512
FIR; Image enhancement; Image fusion; NIR; RGBD BibRef

Shrivastava, A.[Ashish], Rastegari, M.[Mohammad], Shekhar, S.[Sumit], Chellappa, R.[Rama], Davis, L.S.[Larry S.],
Class consistent multi-modal fusion with binary features,
CVPR15(2282-2291)
IEEE DOI 1510
BibRef

Huo, J.[Jie], Wang, G.H.[Guang-Hui], Wu, Q.M.J.[Q.M. Jonathan], Thangarajah, A.[Akilan],
Label Fusion for Multi-atlas Segmentation Based on Majority Voting,
ICIAR15(100-106).
Springer DOI 1507
BibRef

Kasiri, K.[Keyvan], Fieguth, P.W.[Paul W.], Clausi, D.A.[David A.],
Self-similarity measure for multi-modal image registration,
ICIP16(4498-4502)
IEEE DOI 1610
BibRef
Earlier:
Structural Representations for Multi-modal Image Registration Based on Modified Entropy,
ICIAR15(82-89).
Springer DOI 1507
Brain. BibRef

Wang, S.[Sheng], Gu, X.J.[Xing-Jian], Lu, J.F.[Jian-Feng], Yang, J.Y.[Jing-Yu], Wang, R.L.[Rui-Li], Yang, J.[Jian],
Unsupervised Discriminant Canonical Correlation Analysis for Feature Fusion,
ICPR14(1550-1555)
IEEE DOI 1412
Algorithm design and analysis BibRef

Lebedev, M.A., Stepaniants, D.G., Komarov, D.V., Vygolov, O.V., Vizilter, Y.V., Zheltov, S.Y.,
A real-time photogrammetric algorithm for sensor and synthetic image fusion with application to aviation combined vision,
PCV14(171-175).
DOI Link 1404
BibRef

Tan, X.[Xiao], Sun, C.M.[Chang-Ming], Wang, D.[Dadong], Guo, Y.[Yi], Pham, T.D.[Tuan D.],
Soft Cost Aggregation with Multi-resolution Fusion,
ECCV14(V: 17-32).
Springer DOI 1408
BibRef

Amer, M.R.[Mohamed R.], Siddiquie, B.[Behjat], Khan, S.[Saad], Divakaran, A.[Ajay], Sawhney, H.S.[Harpreet S.],
Multimodal fusion using dynamic hybrid models,
WACV14(556-563)
IEEE DOI 1406
Computational modeling BibRef

Levine, S.[Stacey], Heaps, K.[Katie], Koslosky, J.[Joshua], Sidle, G.[Glenn],
Image Fusion using Gaussian Mixture Models,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Koch, M.W.[Mark W.],
One-Class Multiple-Look Fusion: A Theoretical Comparison of Different Approaches with Examples from Infrared Video,
PBVS13(342-347)
IEEE DOI 1309
Infrared video; Multilook fusion; One class classifier Classification not just from single image, but video. Almost super-resolution, but more like data fusion. BibRef

Chen, B.[Bo], Yu, L.[Li], Zhang, W.A.[Wen-An], Song, H.[Haiyu],
Networked multi-sensor fusion estimation with delays, packet losses and missing measurements,
ICARCV12(695-700).
IEEE DOI 1304
BibRef

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IEEE DOI 1302
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Automated Multi-source Remote Sensing Image Registration Based On Phase Congruency,
ISPRS12(XXXIX-B6:189-194).
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Forsberg, D.[Daniel], Farnebäck, G.[Gunnar], Knutsson, H.[Hans], Westin, C.F.[Carl-Fredrik],
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WBIR12(40-49).
Springer DOI 1208
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Elhassouny, A.[Azeddine], Idbraim, S.[Soufiane], Bekkarri, A.[Aissam], Mammass, D.[Driss], Ducrot, D.[Danielle],
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ICISP12(56-64).
Springer DOI 1208
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Yushkevich, P.A.[Paul A.], Wang, H.Z.[Hong-Zhi], Pluta, J.B.[John B.], Avants, B.B.[Brian B.],
From label fusion to correspondence fusion: A new approach to unbiased groupwise registration,
CVPR12(956-963).
IEEE DOI 1208
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Haji-Abolhassani, A.[Amin], Clark, J.J.[James J.],
Information Fusion in Visual-Task Inference,
CRV12(48-55).
IEEE DOI 1207
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Chang, K.Y.[Kai-Yueh], Liu, T.L.[Tyng-Luh], Chen, H.T.[Hwann-Tzong], Lai, S.H.[Shang-Hong],
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IEEE DOI 1201
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Cai, C.F.[Cai-Fang], Mohammad-Djafari, A.[All], Legoupil, S.[Samuel], Rodet, T.[Thomas],
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ICIP11(1377-1380).
IEEE DOI 1201
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Yuan, J.[Jing], Shi, J.[Juan], Tai, X.C.[Xue-Cheng], Boykov, Y.Y.[Yuri Y.],
A Study on Convex Optimization Approaches to Image Fusion,
SSVM11(122-133).
Springer DOI 1201
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Patil, U.[Ujwala], Mudengudi, U.[Uma],
Image fusion using hierarchical PCA.,
ICIIP11(1-6).
IEEE DOI 1112
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Hol, J.D., Schon, T.B., Gustafsson, F.,
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ICARCV08(1857-1862).
IEEE DOI 1109
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Hanmandlu, M.[Madasu], Grover, J.[Jyotsana], Madasu, V.[Vamsi],
Decision Level Fusion Using t-Norms,
DICTA10(33-38).
IEEE DOI 1012
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Han, S.H.[Seung-Han], Koo, B.J.[Bon-Jung], Hutter, A., Shet, V., Stechele, W.,
Subjective Logic Based Hybrid Approach to Conditional Evidence Fusion for Forensic Visual Surveillance,
AVSS10(337-344).
IEEE DOI 1009
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Hitzler, P.[Pascal],
Towards Reasoning Pragmatics,
GS09(9-25).
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A new decision fusion technique for image classification,
ICIP09(2189-2192).
IEEE DOI 0911
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Dey, C., Jia, X.P.[Xiu-Ping], Fraser, D.,
Decision Fusion for Reliable Flood Mapping Using Remote Sensing Images,
DICTA08(184-190).
IEEE DOI 0812
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Tian, H.[Hui], Wang, B.B.[Bin-Bin],
Discussion and Analyze on Image Fusion Technology,
ICMV09(246-250).
IEEE DOI 0912
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Qin, T.L.[Tai-Long], Cheng, H.[Hang], Chen, F.F.[Fa-Fa],
Research on Multi-Sensor Information Fusion Technique for Motor Fault Diagnosis,
CISP09(1-4).
IEEE DOI 0910
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Wu, J.H.[Jian-Hong], Zhang, H.C.[Hong-Cai],
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IEEE DOI 0910
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Rizvi, S.A., Nasrabadi, N.M.,
Fusion techniques for automatic target recognition,
AIPR03(27-32).
IEEE DOI 0310
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Fay, D.A., Ivey, R.T., Bomberger, N., Waxman, A.M.,
Multisensor and spectral image fusion and mining: From neural systems to applications,
AIPR03(11-20).
IEEE DOI 0310
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Blake, P.L., Brown, T.W.,
Quantitative fusion of performance results from actual and simulated image data,
AIPR03(99-102).
IEEE DOI 0310
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Hall, D.L.,
Perspectives on the fusion of image and non-image data,
AIPR03(217-220).
IEEE DOI 0310
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Ma, C.Y.[Cheng-Yuan], Lee, C.H.[Chin-Hui],
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ICPR08(1-4).
IEEE DOI 0812
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Minor, C.P.[Christian P.], Johnson, K.J.[Kevin J.], Rose-Pehrsson, S.L.[Susan L.], Owrutsky, J.C.[Jeffrey C.], Wales, S.C.[Stephen C.], Steinhurst, D.A.[Daniel A.], Gottuk, D.T.[Daniel T.],
Data fusion with a multisensor system for damage control and situational awareness,
AVSBS07(313-317).
IEEE DOI 0709
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Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Probabilistic Combination of Visual Cues for Object Classification,
ISVC07(I: 662-671).
Springer DOI 0711
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Joshi, D.[Dhiraj], Naphade, M.R.[Milind R.], Natsev, A.P.[Apostol P.],
A Greedy Performance Driven Algorithm for Decision Fusion Learning,
ICIP07(VI: 25-28).
IEEE DOI 0709
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Jiang, W.[Wei], Chang, S.F.[Shih-Fu], Loui, A.C.,
Active Context-Based Concept Fusion with Partial User Labels,
ICIP06(2917-2920).
IEEE DOI 0610
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Zhu, Q.Y.[Qiu-Yu], Huang, S.J.[Su-Juan],
Data Fusion and Confidence Measure in Image Feature Detection,
AVSBS06(75-75).
IEEE DOI 0611
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Jayaweera, S.K., Al-Tarazi, K.,
Large System Decision Fusion Performance in Inhomogeneous Sensor Networks,
AVSBS06(72-72).
IEEE DOI 0611
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Wimalajeewa, T., Jayaweera, S.K.,
Optimal Power Scheduling for Data Fusion in Inhomogeneous Wireless Sensor Networks,
AVSBS06(73-73).
IEEE DOI 0611
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Arif, M., Brouard, T., Vincent, N.,
A fusion methodology based on Dempster-Shafer evidence theory for two biometric applications,
ICPR06(IV: 590-593).
IEEE DOI 0609
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Lin, D.[Dahua], Tang, X.[Xiaoou],
Conditional Infomax Learning: An Integrated Framework for Feature Extraction and Fusion,
ECCV06(I: 68-82).
Springer DOI 0608
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Hoppe, F.[Florian], Sommer, G.[Gerald],
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ICPR06(III: 1208-1211).
IEEE DOI 0609
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And: ICPR06(IV: 951).
IEEE DOI 0609
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Dong, W.[Wen], and Pentland, A.P.[Alex P.],
Multi-sensor Data Fusion Using the Influence Model,
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Mahmoud, S.,
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ICIP04(V: 3347-3350).
IEEE DOI 0505
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Wu, G.[Gang], Pan, C.H.[Chun-Hong], Prinet, V., Ma, S.D.[Song-De],
A land use classification method based on region and edge information fusion,
ICIP04(III: 1719-1722).
IEEE DOI 0505
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Wu, H.,
Sensor Fusion for Context-Aware Computing Using Dempster-Shafer Theory,
CMU-RI-TR-03-52, December, 2003. BibRef 0312 Ph.D.Thesis.
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Kahler, O., Denzler, J., Triesch, J.,
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Southwest04(216-220).
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CVPR04(II: 578-585).
IEEE DOI 0408
Information fusion. BibRef

Comaniciu, D.,
Nonparametric information fusion for motion estimation,
CVPR03(I: 59-66).
IEEE DOI 0307
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Comaniciu, D.,
Density estimation-based information fusion for multiple motion computation,
Motion02(241-246).
IEEE DOI 0303
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Gurevich, I.B., Jemova, I.A., Smetanin, Y.G.,
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Garg, A., Agarwal, S., Huang, T.S.,
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Towards Real-Time Cue Integration by Using Partial Results,
ECCV02(IV: 327 ff.).
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Sherrah, J.[Jamie], Gong, S.G.[Shao-Gang],
Continuous Global Evidence-Based Bayesian Modality Fusion for Simultaneous Tracking of Multiple Objects,
ICCV01(II: 42-49).
IEEE DOI 0106
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Earlier:
Fusion of Perceptual Cues using Covariance Estimation,
BMVC99(Movement and Tracking).
PDF File. BibRef

Pan, H.[Hao], Liang, Z.P.[Zhi-Pei], Huang, T.S.[Thomas S.],
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CVPR99(II: 407-412).
IEEE DOI Bayesian framework. BibRef 9900

Pan, H., Liang, Z.P., Anastasio, T.J., Huang, T.S.,
A hybrid NN-Bayesian architecture for information fusion,
ICIP98(I: 368-371).
IEEE DOI 9810
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Bräutigam, C.G.[Carsten G.], Eklundh, J.O.[Jan-Olof], Christensen, H.I.[Henrik I.],
A Model-Free Voting Approach for Integrating Multiple Cues,
ECCV98(I: 734).
Springer DOI BibRef 9800

Hutber, D., Zhang, Z.,
A Two-Stage Approach to Multi-Sensor Temporal Data Fusion,
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Proesmans, M., Pauwels, E.J., Van Gool, L.J., Moons, T., Oosterlinck, A.,
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CVPR93(680-681).
IEEE DOI 0403
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Pinz, A., Bartl, R.,
Information Fusion In Image Understanding,
ICPR92(I:366-370).
IEEE DOI BibRef 9200

Orr, M.J.L., Hallam, J., Fisher, R.B.,
Fusion Through Interpretation,
ECCV92(801-805).
Springer DOI BibRef 9200 Edinburgh BibRef

Booth, D.M., Thacker, N.A., Mayhew, J.E.W., Pidcock, M.K.,
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BMVC91(xx-yy).
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From several vision modules. BibRef

McKendall, R., Mintz, M.,
Non-Monotonic Decision Rules for Sensor Fusion,
DARPA90(874-880). BibRef 9000

Kamberova, G., and Mintz, M.,
Robust Multi-Sensor Fusion: A Decision-Theoretic Approach,
DARPA90(867-873). BibRef 9000

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Image and Sensor Fusion -- IR and Thermal with Visible .


Last update:May 25, 2017 at 22:18:08