13.6 Knowledge-Based Vision

Chapter Contents (Back)
Recognition, Model Based. Model Based Recognition. Object Recognition. Matching, Models. Knowledge. High Level Vision.

13.6.1 General Issues -- Knowledge-Based Vision

Chapter Contents (Back)
Matching, Models. Knowledge. Knowledge-Based Vision.
See also Context, Fine-Grained Classification.

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CandT(251-268), 1963. BibRef 6300
Earlier: WJCC(19), 1961, pp. 555-570. Recognition using a series of operators (patterns, binary masks). BibRef

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Elsevier DOI 0309
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Earlier:
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CVS78(363-377). BibRef
Earlier:
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IJCAI77(597). BibRef

Uhr, L.,
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ICPR76(287-293). BibRef 7600

Uhr, L.[Leonard],
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Elsevier DOI 0309
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Elsevier DOI 0309
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CGIP(12), No. 4, April 1980, pp. 407-425.
Elsevier DOI BibRef 8004

Barrow, H.G., and Tenenbaum, J.M.,
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SRI AICenterTN 108, 1975. BibRef 7500
And: SRI AIMemo121, April 1976. Knowledge-Based Vision. System: MSYS. The MSYS Report. Use inexact reasoning on uncertain data to interpret regions extracted from an image. MSYS is an asynchronous relaxation process that applies the rules imposed by the modeluntil the labels are consistent. Constraints such as surface height and orientation can bu used. Relations between objects in the scene (hence regions in the image) can be used.. An M* (modified A*) search is used. For application in IGS:
See also Experiments in Interpretation Guided Segmentation. BibRef

Kunii, T.L., Weyl, S., Tenenbaum, J.M.,
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ICPR74(310-316). BibRef 7400

Tenenbaum, J.M., Weyl, S.,
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IJCAI75(682-687). BibRef 7500

Tenenbaum, J.M.,
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CGIP(2), No. 3, December 1973, pp. 308-320. BibRef 7312
And: SRI-TN-84, 1973. Early version of old SRI work. A good reference for basic techniques for description based extraction. BibRef

Tenenbaum, J.M.,
Object Recognition in Multi-Sensory Scene Analysis,
SRI AIMemo84, September 1973. Acquisition and validation. Turned into MSYS and related work. BibRef 7309

Nitzan, D.,
Object Recognition in Multisensory Scene Analysis,
SRI AIMemo83, November 1973. BibRef 7311

Garvey, T.D.,
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SRITechnical Note 117, September 1976. BibRef 7609

Garvey, T.D., and Tenenbaum, J.M.,
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ICPR74(162-168). Another of the early papers. BibRef 7400

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PR(14), No. 1-6, 1981, pp. 111-115.
Elsevier DOI 0309
BibRef

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Elsevier DOI BibRef 8400
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van Cleynenbruegel, J., Fierens, F., Suetens, P., Oosterlinck, A.,
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IVC(6), No. 4, November 1988, pp. 238-246.
Elsevier DOI BibRef 8811

Chen, S.,
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IJIS(1), 1986, pp. 15-28. BibRef 8600

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AIMag(9), No. 2, Summer 1988, pp. 75-94. BibRef 8800
And: ASR-I90(Ch. 4). BibRef
And:
A Production System Environment for Integrating Knowledge with Vision Data,
SRMSF87(1-12). Blackboard. BibRef

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Elsevier DOI BibRef 8905

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SMC(20), No. 6, November/December, 1990, pp. 1285-1300. BibRef 9011
Earlier:
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SMC-C89(xx-yy). Pose Estimation. BibRef

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Elsevier DOI BibRef 8908

Rosin, P.L.[Paul L.], Ellis, T.[Tim],
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Ellis, T.J., Rosin, P.L., and Golton, P.,
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Lee, C.M., Pong, T.C., Slagle, J.R.,
A Knowledge-Based System for the Image Correspondence Problem,
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Meisels, A.,
Levels of Knowledge for Object Extraction,
MVA(4), 1991, pp. 183-192. BibRef 9100

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Kakusho, K., Dan, S., Abe, N., and Kitahashi, T.,
Shape Recovery and Error Correction Based on Hypothetical Constraints by Parallel Network for Energy Minimization,
PRAI(8), 1994, pp. 577-593. BibRef 9400

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AIMag(15), No. 1, Spring 1994, pp. 26-38. BibRef 9400

Eklundh, J.O.,
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Wallace, A.M.[Andrew M.],
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PR(21), No. 3, 1988, pp. 241-259.
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Grenander, U.[Ulf], Miller, M.I.,
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Aviad, Z., Lozinskii, E.,
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Pham, D.T., Dimov, S.S.,
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Edelman, S., Duvdevani-Bar, S.,
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NeurComp(9), No. 4, May 15 1997, pp. 701-720. 9706
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Duvdevani-Bar, S.[Sharon], Edelman, S.[Shimon],
Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes,
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Mirmehdi, M., Palmer, P.L., Kittler, J.V., Dabis, H.S.,
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IP(8), No. 8, August 1999, pp. 1084-1101.
IEEE DOI BibRef 9908
Earlier:
Multi-pass Feedback Control for Object Recognition,
VI96(49-56).
PS File. BibRef
Earlier:
Complex Feedback Strategies for Hypothesis Generation and Verification,
BMVC96(Poster Session 1). 9608
Optimization technique with feedback. University of Surrey BibRef

Lesser, V.R.[Victor R.], Nawab, H.[Hamid], Klassner, F.I.[Frank I.],
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AI(77), No. 1, October 1995, pp. 129-171.
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Kelly, M.F.[Michael F.], and Levine, M.D.[Martin D.],
Finding and Describing Objects in Complex Images,
AIU96(209-226). Descriptions, Parts. Various filter/operators on the images. BibRef 9600

Bourbakis, N.G., Mertoguno, J.S.,
Kydon: An Autonomous, Multilayer Image-Understanding System - Lower Layers,
EngAAI(9), No. 1, February 1996, pp. 43-52. BibRef 9602

Roli, F., Serpico, S.B., Vernazza, G.,
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PIEEE(84), No. 11, November 1996, pp. 1659-1681. 9611
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Dellepiane, S.G., Venturi, G., Vernazza, G.L.,
Model Generation and Model Matching of Real Images by a Fuzzy Approach,
PR(25), No. 2, February 1992, pp. 115-137.
Elsevier DOI BibRef 9202

Dellepiane, S.G., Serpico, S.B., Vernazza, G.L.,
Analysis and Classification of SAR Images by a Knowledge-Based Approach,
ICPR88(II: 1207-1209).
IEEE DOI BibRef 8800

Kuruppu, N.R.,
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PRL(17), No. 11, September 16 1996, pp. 1151-1155. 9611
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Gamage, L.B., Gosine, R.G., de Silva, C.W.,
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SMC-A(26), No. 1, January 1996, pp. 105-120.
IEEE Top Reference. BibRef 9601

Chan, S.W.K., Leung, K.S., Wong, W.S.F.,
Object-Oriented Knowledge-Based System for Image Diagnosis,
AppAI(10), No. 5, September/October 1996, pp. 407-438. 9611
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Kontoes, C.C., Rokos, D.,
The Integration of Spatial Context Information in an Experimental Knowledge-Based System and the Supervised Relaxation Algorithm: 2 Successful Approaches to Improving Spot-Xs Classification,
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Moody, J.[John], Flynn, P.J.[Patrick J.], Cohn, D.L.[David L.],
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Earlier: ICPR92(IV:107-110).
IEEE DOI 9208
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Tönjes, R., Growe, S., Bückner, J., Liedtke, C.E.,
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Draper, B.A.[Bruce A.], Bins, J.[Jose], Baek, K.[Kyungim],
ADORE: Adaptive Object Recognition,
Videre(1), No. 4, Winter 2000, pp. xx-yy. 0005
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Earlier: CVS99(522 ff.).
Springer DOI 0209
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Draper, B.A.[Bruce A.], Baek, K.[Kyungim], Boody, J.[Jeff],
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Springer DOI 0501
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Earlier: CVS03(1 ff).
Springer DOI 0306
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Drummond, T.W.[Tom W.], Caelli, T.M.[Terry M.],
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CVIU(80), No. 3, December 2000, pp. 315-348.
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Caelli, T.M.[Terry M.], and Bischof, W.F.[Walter F.],
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Blake, R.E.[Richard E.], Juozapavicius, A.[Algimantas],
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See also Graph image language techniques supporting radiological, hand image interpretations. BibRef

Rosin, P.L.[Paul L.], Rana, O.F.[Omer F.],
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Neumann, B.[Bernd], Möller, R.[Ralf],
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Elsevier DOI 0711
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Springer DOI 0310
Scene interpretation; Description logics; High-level vision BibRef

Schroeder, C.[Carsten], Neumann, B.[Bernd],
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Hogg, D.C.[David C.], Neumann, B.[Berndt],
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Ponce, J.[Jean], Hebert, M.[Martial], Schmid, C.[Cordelia], and Zisserman, A.[Andrew], (Eds.)
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Treiber, M.A.[Marco Alexander],
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Springer2010, ISBN: 978-1-84996-234-6
WWW Link. Algorithm descriptions. Buy this book: An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications (Advances in Pattern Recognition) 1010
BibRef

Kleiner, I.[Igor], Keren, D.[Daniel], Newman, I.[Ilan], Ben-Zwi, O.[Oren],
Applying Property Testing to an Image Partitioning Problem,
PAMI(33), No. 2, February 2011, pp. 256-265.
IEEE DOI 1101
Quick test to determine whether to continue analysis. BibRef

Hata, S.[Seiji],
Tailor-made engineering in image processing industry,
FCV11(1-2).
IEEE DOI 1102
To date computer vision applications are custom made. Discuss attempts to improve this. BibRef

Falomir, Z.[Zoe], Museros, L.[Lledó], Gonzalez-Abril, L.[Luis], Escrig, M.T.[M. Teresa], Ortega, J.A.[Juan A.],
A model for the qualitative description of images based on visual and spatial features,
CVIU(116), No. 6, June 2012, pp. 698-714.
Elsevier DOI 1204
Qualitative shape; Qualitative colours; Qualitative orientation; Spatial description Main visual features (shape and color) and the main spatial features (fixed orientation, relative orientation and topology) of each object within the image. BibRef

Sanz, I.[Ismael], Museros, L.[Lledó], Falomir, Z.[Zoe], Gonzalez-Abril, L.[Luis],
Customising a qualitative colour description for adaptability and usability,
PRL(67, Part 1), No. 1, 2015, pp. 2-10.
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Colour naming
See also Measures of similarity between qualitative descriptions of shape, colour and size applied to mosaic assembling. BibRef

Falomir, Z.[Zoe], Museros, L.[Lledó], Castelló, V.[Vicent], Gonzalez-Abril, L.[Luis],
Qualitative distances and qualitative image descriptions for representing indoor scenes in robotics,
PRL(34), No. 7, 1 May 2013, pp. 731-743.
Elsevier DOI 1303
Sensor data integration; Fuzzy logic; Qualitative shape; Qualitative colour; Topology; Qualitative spatial orientation BibRef

Li, C.C.[Cong-Cong], Kowdle, A.[Adarsh], Saxena, A.[Ashutosh], Chen, T.H.[Tsu-Han],
Toward Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models,
PAMI(34), No. 7, July 2012, pp. 1394-1408.
IEEE DOI 1205
Scene understanding, classification, machine learning, robotics. Jointly optimize depth, categorization, object detection. BibRef

Moghaddam, R.F., Cheriet, M.,
Real-Time Knowledge-Based Processing of Images: Application of the Online NLPM Method to Perceptual Visual Analysis,
IP(21), No. 8, August 2012, pp. 3390-3404.
IEEE DOI 1208
BibRef

Yu, L., Xie, J., Chen, S.,
Conditional random field-based image labelling combining features of pixels, segments and regions,
IET-CV(6), No. 5, 2012, pp. 459-467.
DOI Link 1210
Single layer segment based CRF method. BibRef

Maji, S.[Subhransu], Berg, A.C.[Alexander C.], Malik, J.[Jitendra],
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PAMI(35), No. 1, January 2013, pp. 66-77.
IEEE DOI 1212
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Zhang, H.[Hao], Berg, A.C.[Alexander C.], Maire, M.[Michael], Malik, J.[Jitendra],
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CVPR06(II: 2126-2136).
IEEE DOI 0606
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Ordonez, V.[Vicente], Liu, W.[Wei], Deng, J.[Jia], Choi, Y.[Yejin], Berg, A.C.[Alexander C.], Berg, T.L.[Tamara L.],
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DOI Link 1604
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Chen, X.W.[Xiao-Wu], Li, Q.[Qing], Zhao, D.Y.[Dong-Yue], Zhao, Q.P.[Qin-Ping],
Occlusion cues for image scene layering,
CVIU(117), No. 1, January 2013, pp. 42-55.
Elsevier DOI 1212
Human perception; Occlusion cues; Occlusion prediction; Layering BibRef

Yue, P.[Peng], Di, L.P.[Li-Ping], Wei, Y.X.[Ya-Xing], Han, W.G.[Wei-Guo],
Intelligent services for discovery of complex geospatial features from remote sensing imagery,
PandRS(83), No. 1, 2013, pp. 151-164.
Elsevier DOI 1308
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Pavlidis, T.[Theo],
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Quinton, J.C., Volpi, N.C., Barca, L., Pezzulo, G.,
The Cat is on the Mat. or is it a Dog? Dynamic Competition in Perceptual Decision Making,
SMCS(44), No. 5, May 2014, pp. 539-551.
IEEE DOI 1405
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Smith, J.R.[John R.],
How Many Visual Concepts?,
MultMedMag(21), No. 1, January 2014, pp. 2-3.
IEEE DOI 1405
Scene analysis BibRef

Xie, Y.R.[Yu-Rui], Wu, Q.B.[Qing-Bo], Luo, B.[Bing], Huang, C.[Chao], Tang, L.Z.[Liang-Zhi],
A Combing Top-Down and Bottom-Up Discriminative Dictionaries Learning for Non-specific Object Detection,
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Xie, Y.R.[Yu-Rui], Wu, Q.B.[Qing-Bo], Luo, B.[Bing],
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Sun, M.[Min], Kim, B.S.[Byung-Soo], Kohli, P.[Pushmeet], Savarese, S.[Silvio],
Relating Things and Stuff via ObjectProperty Interactions,
PAMI(36), No. 7, July 2014, pp. 1370-1383.
IEEE DOI 1407
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Earlier: A2, A1, A3, A4:
Relating Things and Stuff by High-Order Potential Modeling,
Global12(III: 293-304).
Springer DOI 1210
Detectors. the object and background. BibRef

Wang, S.[Shuo], Wang, Y.Z.[Yi-Zhou],
Weakly Supervised Semantic Segmentation with a Multiscale Model,
SPLetters(22), No. 3, March 2015, pp. 308-312.
IEEE DOI 1410
Buildings BibRef

Wang, S.[Shuo], Wang, Y.Z.[Yi-Zhou], Zhu, S.C.[Song-Chun],
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IEEE DOI 1512
BibRef
Earlier:
Hierarchical Space Tiling for Scene Modeling,
ACCV12(II:796-810).
Springer DOI 1304
attribute grammars BibRef

Wang, S.[Shuo], Joo, J.[Jungseock], Wang, Y.Z.[Yi-Zhou], Zhu, S.C.[Song-Chun],
Weakly Supervised Learning for Attribute Localization in Outdoor Scenes,
CVPR13(3111-3118)
IEEE DOI 1309
Hierarchical Space Tiling (HST). Learn parts and attributs given captions. BibRef

Aloimonos, Y.[Yiannis], Fermüller, C.[Cornelia],
The Cognitive Dialogue: A new model for vision implementing common sense reasoning,
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Elsevier DOI 1502
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Aditya, S.[Somak], Yang, Y.Z.[Ye-Zhou], Baral, C.[Chitta], Aloimonos, Y.[Yiannis], Fermüller, C.[Cornelia],
Image Understanding using vision and reasoning through Scene Description Graph,
CVIU(173), 2018, pp. 33-45.
Elsevier DOI 1901
Image Understanding, Commonsense Reasoning, Vision, Reasoning BibRef

Guo, R.Q.[Rui-Qi], Hoiem, D.[Derek],
Labeling Complete Surfaces in Scene Understanding,
IJCV(112), No. 2, April 2015, pp. 172-187.
WWW Link. 1504
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Earlier:
Beyond the Line of Sight: Labeling the Underlying Surfaces,
ECCV12(V: 761-774).
Springer DOI 1210
infer hidden regions BibRef

Lindner, A.[Albrecht], Susstrunk, S.,
Semantic-Improved Color Imaging Applications: It Is All About Context,
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IEEE DOI 1505
Computer vision BibRef

Lindner, A.[Albrecht],
Semantic Awareness for Automatic Image Interpretation,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
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Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Feng, J.S.[Jian-Shi], Jia, K., Huang, Z.Y.[Zhong-Yang], Yan, S.C.[Shui-Cheng],
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IEEE DOI 1508
Data mining BibRef

Dong, J.[Jian], Xia, W.[Wei], Chen, Q.A.[Qi-Ang], Feng, J.S.[Jian-Shi], Huang, Z.Y.[Zhong-Yang], Yan, S.C.[Shui-Cheng],
Subcategory-Aware Object Classification,
CVPR13(827-834)
IEEE DOI 1309
Ambiguity Modeling; Classification; Subcategory Mining BibRef

Liu, X.H.[Xiong-Hao], Yang, W.[Wei], Lin, L.[Liang], Wang, Q.[Qing], Cai, Z.Q.[Zhao-Quan], Lai, J.H.[Jian-Huang],
Data-Driven Scene Understanding with Adaptively Retrieved Exemplars,
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IEEE DOI 1508
Computer graphics. Recover examples from database, then propogate pixel labels. BibRef

Zitnick, C.L.[C. Lawrence], Vedantam, R.[Ramakrishna], Parikh, D.[Devi],
Adopting Abstract Images for Semantic Scene Understanding,
PAMI(38), No. 4, April 2016, pp. 627-638.
IEEE DOI 1603
Abstracts BibRef

Vedantam, R.[Ramakrishna], Lin, X.[Xiao], Batra, T.[Tanmay], Zitnick, C.L.[C. Lawrence], Parikh, D.[Devi],
Learning Common Sense through Visual Abstraction,
ICCV15(2542-2550)
IEEE DOI 1602
Cognition. More than just text. BibRef

Fang, Q., Xu, C.S.[Chang-Sheng], Sang, J., Hossain, M.S.[M. Shamim], Ghoneim, A.[Ahmed],
Folksonomy-Based Visual Ontology Construction and Its Applications,
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IEEE DOI 1604
Computational modeling BibRef

Yang, X.S.[Xiao-Shan], Zhang, T.Z.[Tian-Zhu], Xu, C.S.[Chang-Sheng], Yan, S.C.[Shui-Cheng], Hossain, M.S.[M. Shamim], Ghoneim, A.[Ahmed],
Deep Relative Attributes,
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CVPR21(1356-1365)
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CVPR21(6899-6908)
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Progressive Knowledge-Embedded Unified Perceptual Parsing for Scene Understanding,
MULA21(1633-1642)
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Deep learning, Visualization, Organizations, Knowledge representation, Logic gates BibRef

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AUVi21(1553-1561)
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Deep learning, Visualization, Image recognition, Psychology, Motion pictures BibRef

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CVPR20(13883-13892)
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CVPR20(13447-13456)
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CVPR20(10073-10082)
IEEE DOI 2008
Convolution, Image recognition, Computational modeling, Robustness, Tensile stress, Standards BibRef

Luo, G., Zhou, Y., Sun, X., Cao, L., Wu, C., Deng, C., Ji, R.,
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CVPR20(10031-10040)
IEEE DOI 2008
Task analysis, Feature extraction, Frequency modulation, Visualization, Collaborative work, Tensile stress, Linguistics BibRef

Chen, Z., Wang, P., Ma, L., Wong, K.K., Wu, Q.,
Cops-Ref: A New Dataset and Task on Compositional Referring Expression Comprehension,
CVPR20(10083-10092)
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Cognition, Visualization, Task analysis, Cats, Engines, Semantics, Genetic expression BibRef

Liao, Y., Liu, S., Li, G., Wang, F., Chen, Y., Qian, C., Li, B.,
A Real-Time Cross-Modality Correlation Filtering Method for Referring Expression Comprehension,
CVPR20(10877-10886)
IEEE DOI 2008
Correlation, Feature extraction, Visualization, Proposals, Kernel, Heating systems, Filtering BibRef

Eum, S., Han, D., Briggs, G.,
SomethingFinder: Localizing undefined regions using referring expressions,
MVM20(1551-1554)
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Yang, S., Li, G., Yu, Y.,
Graph-Structured Referring Expression Reasoning in the Wild,
CVPR20(9949-9958)
IEEE DOI 2008
Cognition, Visualization, Semantics, Linguistics, Grounding, Layout, Image edge detection BibRef

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Wu, H.[Hao], Mao, J.Y.[Jia-Yuan], Zhang, Y.[Yufeng], Jiang, Y.N.[Yu-Ning], Li, L.[Lei], Sun, W.W.[Wei-Wei], Ma, W.Y.[Wei-Ying],
Unified Visual-Semantic Embeddings: Bridging Vision and Language With Structured Meaning Representations,
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Semantic Bottleneck for Computer Vision Tasks,
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ECCV18(XIII: 37-53).
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ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking,
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Attributes as Operators: Factorizing Unseen Attribute-Object Compositions,
ECCV18(I: 172-190).
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Goal-Oriented Visual Question Generation via Intermediate Rewards,
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Learning Robust Object Recognition Using Composed Scenes from Generative Models,
CRV17(232-239)
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convolution, feature extraction, feedforward neural nets, image classification, image representation, visual cortex BibRef

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Motivation Design Methodology for Online Knowledge Sharing Interface,
IVIC17(224-232).
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High-Level Concepts for Affective Understanding of Images,
WACV17(679-687)
IEEE DOI 1609
Analytical models, Feature extraction, Information technology, Multimedia communication, Neural networks, Predictive models, Support, vector, machines BibRef

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Building semantic understanding beyond deep learning from sound and vision,
ICPR16(2097-2102)
IEEE DOI 1705
Computational modeling, Feature extraction, Generators, Histograms, Semantics, Support vector machines, Visualization BibRef

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Auto-Illustrating Poems and Songs with Style,
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A Task-Oriented Approach for Cost-Sensitive Recognition,
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IEEE DOI 1612
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CVPR16(203-212)
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CVPR16(11-20)
IEEE DOI 1612
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ECCV16(I: 852-869).
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Yu, L.C.[Li-Cheng], Poirson, P.[Patrick], Yang, S.[Shan], Berg, A.C.[Alexander C.], Berg, T.L.[Tamara L.],
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Mbock, E.A.M.[Etienne Aubin Mbe],
Image reconstruction using the reconfiguration technique,
AIPR15(1-9)
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feature extraction BibRef

Klarin, K., Celar, S.,
Modeling information resources and application using ontological engineering,
ICCVIA15(1-6)
IEEE DOI 1603
ontologies (artificial intelligence) BibRef

Sun, C.[Chen], Gan, C.[Chuang], Nevatia, R.[Ram],
Automatic Concept Discovery from Parallel Text and Visual Corpora,
ICCV15(2596-2604)
IEEE DOI 1602
Bicycles; Detectors; Roads; Semantics; Visualization; Vocabulary BibRef

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Intangible Cultural Heritage BibRef

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CVS11(1-10).
Springer DOI 1109
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Sherrah, J.[Jamie],
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ACIVS10(I: 414-425).
Springer DOI 1012
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Kulikowski, J.L.[Juliusz L.],
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ICCVG10(I: 43-58).
Springer DOI 1009
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Wang, G.[Gang], Gallagher, A.C.[Andrew C.], Luo, J.B.[Jie-Bo], Forsyth, D.A.[David A.],
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Satkin, S.[Scott], Hebert, M.[Martial],
3DNN: Viewpoint Invariant 3D Geometry Matching for Scene Understanding,
ICCV13(1873-1880)
IEEE DOI 1403
3D Data BibRef

Satkin, S.[Scott], Lin, J.[Jason], Hebert, M.[Martial],
Data-Driven Scene Understanding from 3D Models,
BMVC12(128).
DOI Link 1301
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Gupta, A.[Abhinav], Satkin, S.[Scott], Efros, A.A.[Alexei A.], Hebert, M.[Martial],
From 3D scene geometry to human workspace,
CVPR11(1961-1968).
IEEE DOI 1106
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Gupta, A.[Abhinav], Efros, A.A.[Alexei A.], Hebert, M.[Martial],
Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics,
ECCV10(IV: 482-496).
Springer DOI
WWW Link. 1009
Award, ECCV, HM. Reason about the scene in 3D, objects have volume and 3d relationships. BibRef

Gao, T.S.[Tian-Shi], Koller, D.[Daphne],
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ICCV11(2072-2079).
IEEE DOI 1201
Really need thousands of categories for real world. Multiclass classifier, hierarchical. BibRef

Wang, H.Y.[Hua-Yan], Gould, S.[Stephen], Koller, D.[Daphne],
Discriminative Learning with Latent Variables for Cluttered Indoor Scene Understanding,
CACM(56), No. 4, April 2013, pp. 92-99.
DOI Link 1304
BibRef
Earlier: ECCV10(II: 435-449).
Springer DOI 1009
BibRef
And: ECCV10(IV: 497-510).
Springer DOI 1009
We address the problem of understanding an indoor scene from a single image in terms of recovering the room geometry (floor, ceiling, and walls) and furniture layout. Explain the scene by the object face and the clutter (i.e. what is on top of the desk) BibRef

Liu, B.Y.[Be-Yang], Gould, S.[Stephen], Koller, D.[Daphne],
Single image depth estimation from predicted semantic labels,
CVPR10(1253-1260).
IEEE DOI 1006
First a semantic interpretation, then assign depths.
See also Alphabet SOUP: A framework for approximate energy minimization. BibRef

Huang, Y.Z.[Yong-Zhen], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu], Tao, D.C.[Da-Cheng],
A Novel Visual Organization Based on Topological Perception,
ACCV09(I: 180-189).
Springer DOI 0909
Topological perceptual organization form Chen is a top down recognition process. BibRef

Zhou, B.[Bolei], Zhang, L.Q.[Li-Qing],
Scene Gist: A Holistic Generative Model of Natural Image,
ACCV09(II: 395-404).
Springer DOI 0909
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Yang, X.[Xiong], Wu, T.F.[Tian-Fu], Zhu, S.C.[Song-Chun],
Evaluating information contributions of bottom-up and top-down processes,
ICCV09(1042-1049).
IEEE DOI 0909
Evaluate contribution of B-U or T-D processes. BibRef

Al-Absi, H.R.H.[Hamada R. H.], Abdullah, A.B.[Azween B.],
A Proposed Biologically Inspired Model for Object Recognition,
IVIC09(213-222).
Springer DOI 0911
Integration of the feed-forward and feedback functions in the visual cortex. BibRef

Misra, A., Sowmya, A., Compton, P.,
Impact of quasi-expertise on knowledge acquisition in computer vision,
IVCNZ09(334-339).
IEEE DOI 0911
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Baur, R.[Rafael], Efros, A.A.[Alexei A.], Hebert, M.[Martial],
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CMU-RI-TR-08-43, October, 2008.
WWW Link. BibRef 0810

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ECCV08(IV: 733-747).
Springer DOI 0810
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Chang, S.K.[Shi Kuo],
Virtual Spaces: From the Past to the Future,
Visual08(xx-yy).
Springer DOI 0809
How to look at space. BibRef

Levine, G.[Geoffrey], DeJong, G.[Gerald],
Object Detection by Estimating and Combining High-Level Features,
CIAP09(161-169).
Springer DOI 0909
BibRef
Earlier:
Explanation-Based Object Recognition,
WACV08(1-8).
IEEE DOI 0801
BibRef

Mundy, J.L.[Joseph L.],
Object Recognition in the Geometric Era: A Retrospective,
CLOR06(3-28).
Springer DOI 0711
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Kumar, S., Ramos, F., Douillard, B., Ridley, M., Durrant-Whyte, H.F.,
A Novel Visual Perception Framework,
ICARCV06(1-6).
IEEE DOI 0612
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Sako, H.[Hiroshi],
Recognition Strategies in Machine Vision Applications,
IMVIP07(3-3).
IEEE DOI 0709
BibRef

Tsotsos, J.K.[John K.], Rodriguez-Sanchez, A.J.[Antonio Jose], Rothenstein, A.L.[Albert L.], Simine, E.[Eugene],
Different Binding Strategies for the Different Stages of Visual Recognition,
BVAI07(150-160).
Springer DOI 0710
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Dhua, A.S.[Arnab S.], Cutzu, F.[Florin],
Hierarchical, Generic to Specific Multi-class Object Recognition,
ICPR06(I: 783-788).
IEEE DOI 0609
Generic and specific class recognition. BibRef

Zehnder, P.[Philipp], Koller-Meier, E.[Esther], Van Gool, L.J.[Luc J.],
An Efficient Shared Multi-Class Detection Cascade,
BMVC08(xx-yy).
PDF File. 0809
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Earlier:
Efficient, Simultaneous Detection of Multiple Object Classes,
ICPR06(I: 797-802).
IEEE DOI 0609
Decision (ternary) approach for multiple object classes. BibRef

Kittler, J.V., Christmas, W.J., Kostin, A., Yan, F., Kolonias, I., Windridge, D.,
A Memory Architecture and Contextual Reasoning Framework for Cognitive Vision,
SCIA05(343-358).
Springer DOI 0506
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Nagel, H.H.,
Cognitive Vision Systems: From Ideas to Specifications,
CogVis03(57-69).
Springer DOI 0310
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Nagel, H.H.,
On Sampling the Spectrum of Approaches Toward Cognitive Vision Systems,
CogVis03(315-319).
Springer DOI 0310
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van Kaick, O.M., Mori, G.,
Automatic Classification of Outdoor Images by Region Matching,
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IEEE DOI 0607
Use segmented regions. BibRef

Delage, E., Lee, H.L.[Hong-Lak], Ng, A.Y,
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image,
CVPR06(II: 2418-2428).
WWW Link. Maybe also:
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Knowledge allows us to resolve ambiguities in 3D. BibRef

Georis, B.[Benoit], Maziere, M.[Magale], Bromond, F.[Francois],
Evaluation and Knowledge Representation Formalisms to Improve Video Understanding,
CVS06(27).
IEEE DOI 0602
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Nelson, R.C.[Randal C.],
Generating Verbal Descriptions of Colored Objects: Towards Grounding Language in Perception,
WACV05(I: 46-53).
IEEE DOI 0502
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Li, M.H.[Mu-Hua], Clark, J.J.,
Selective Attention in the Learning of Invariant Representation of Objects,
AttenPerf05(III: 93-93).
IEEE DOI 0507
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Ehtiati, T., Clark, J.J.,
A strongly coupled architecture for contextual object and scene identification,
ICPR04(III: 69-72).
IEEE DOI 0409
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He, X.M.[Xu-Ming], Zemel, R.S.[Richard S.],
Latent topic random fields: Learning using a taxonomy of labels,
CVPR08(1-8).
IEEE DOI 0806
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He, X.M.[Xu-Ming], Zemel, R.S., Carreira-Perpinan, M.A.,
Multiscale conditional random fields for image labeling,
CVPR04(II: 695-702).
IEEE DOI 0408
Context for assigning labels. BibRef

Wunstel, M., Moratz, R.,
Automatic object recognition within an office environment,
CRV04(104-109).
IEEE DOI 0408
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Neumann, B.[Bernd], Weiss, T.[Thomas],
Navigating through Logic-Based Scene Models for High-Level Scene Interpretations,
CVS03(212 ff).
Springer DOI 0306
BibRef

Boukraa, M., Ando, S.,
Tag-based vision: assisting 3D scene analysis with radio-frequency tags,
ICIP02(I: 269-272).
IEEE DOI 0210
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Sadr, J.[Javid], Sinha, P.[Pawan],
Exploring Object Perception with Random Image Structure Evolution,
MIT AI Memo-2001-006, March 2001.
WWW Link. 0105
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Büker, U.,
Cooperative Agents for Object Recognition,
ICPR00(Vol IV: 157-160).
IEEE DOI 0009
High level recognition. BibRef

Weber, M., Welling, M., Perona, P.,
Unsupervised Learning of Models for Recognition,
ECCV00(I: 18-32).
Springer DOI 0003
Award, Koenderink Prize. BibRef

Weber, M., Welling, M., Perona, P.,
Towards Automatic Discovery of Object Categories,
CVPR00(II: 101-108).
IEEE DOI 0005
BibRef

Vu, A.S.,
A computer vision system for automatic knowledge-based configuration of the image processing and hierarchical object recognition,
CIAP99(636-641).
IEEE DOI 9909
BibRef

MacGregor, R.M.[Robert M.], and Russ, T.A.[Thomas A.], and Price, K.E.[Keith E.],
Knowledge Representation for Computer Vision: The VEIL Project,
ARPA94(II:919-927). BibRef 9400 USC Computer Vision BibRef

Russ, T.A., MacGregor, R.M., Salemi, B., Price, K.E., Nevatia, R.,
VEIL: Combining Semantic Knowledge with Image Understanding,
Radius97(409-418). BibRef 9700 USC Computer Vision BibRef
And: ARPA96(373-380). BibRef

Matas, J.G.[Jiri G.], Young, R., Kittler, J.V.[Josef V.],
Hypothesis Selection for Scene Interpretation Using Grammatical Models of Scene Evolution,
ICPR98(Vol II: 1718-1720).
IEEE DOI 9808
BibRef

Oshitani, T.[Tohru], Watanabe, T.[Toyohide],
Parallel Map Recognition Based on Multilayer Partitioned Blackboard Model,
ICPR98(Vol II: 1604-1606).
IEEE DOI 9808
BibRef

Li, D., Munck-Fairwood, R.C.,
A Formal Definition and Framework for Generic Object Recognition,
SCIA93(81-88). BibRef 9300

Burger, W., Burge, M., Mayr, W.,
Learning to recognize generic visual categories using a hybrid structural approach,
ICIP96(II: 321-324).
IEEE DOI 9610
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Lai, G.C., de Figueiredo, R.J.P.,
Image interpretation using contextual feedback,
ICIP95(II: 623-626).
IEEE DOI 9510
BibRef

Shvaytser, H.,
Towards A Computational Theory Of Model Based Vision And Perception,
ICCV90(283-286).
IEEE DOI BibRef 9000

Smyrniotis, C.[Chuck], and Dutta, K.[Kalyan],
A Knowledge-Based System for Recognizing Man-Made Objects in Aerial Images,
CVPR88(111-117).
IEEE DOI Recognize Aerial Images. Preliminary report on Knowledge-Based system to deal with airports. BibRef 8800

Hutchinson, S.A., Cromwell, R.L., and Kak, A.C.,
Applying Uncertainty Reasoning to Model Based Object Recognition,
CVPR89(541-548).
IEEE DOI System level design. BibRef 8900

Cromwell, R.L., and Kak, A.C.,
Automatic Generation of Object Class Descriptions Using Symbolic Learning Techniques,
AAAI-91(710-717). BibRef 9100

Numao, M., Ishizuka, M.,
A Frame-Like Knowledge Representation System for Computer Vision,
ICPR84(1128-1130). BibRef 8400

Shirai, Y.,
Recent Advance in 3-D Scene Analysis,
ICPR78(86-94). Line labeling, structured light, generalized cones, etc. BibRef 7800

Ballard, D.H.[Dana H.], Brown, C.M., and Feldman, J.A.,
An Approach to Knowledge-Directed Scene Analysis,
CVS78(271-281). BibRef 7800
Earlier: IJCAI77(664-670). Hallucinate a rib. BibRef

Bajcsy, R., Joshi, A.K.,
A Partially Ordered World Model and Natural Outdoor Scenes,
CVS78(263-270). BibRef 7800

Levine, M.D.,
A Knowledge-Based Computer Vision System,
CVS78(335-352). BibRef 7800

Segen, J.[Jakub],
Model Learning and Recognition of Nonrigid Objects,
CVPR89(597-602).
IEEE DOI BibRef 8900
Earlier:
Learning Structural Descriptions of Shape,
MVAAS88(XX-YY). BibRef
And: CVPR85(96-99). (AT&T Bell Labs) Learning. Classify and label the parts of non-rigid objects with some occlusions. BibRef

Segen, J.[Jakub],
Learning Shape Models for a Vision Based Human-Computer Interface,
AAAI-MLCV93(xx). A.T.T. Bell Laboratories. BibRef 9300

Bronskill, J.F., Hepburn, J.S.A., and Au, W.K.,
A Knowledge-Based Approach to the Detection, Tracking and Classification of Target Formations in Infrared Image Sequences,
CVPR89(153-158).
IEEE DOI Find point targets and group into clusters to identify. BibRef 8900

Liedtke, C.E., Blomer, A.,
Architecture of the Knowledge Based Configuration System for Image Analysis 'Conny',
ICPR92(I:375-378).
IEEE DOI BibRef 9200

van der Putten, F., Zerubia, J.B.,
A Universal Knowledge-Based Imaging System for Hazardous Environments,
ICPR92(I:211-214).
IEEE DOI BibRef 9200

Boyer, K.L., Safranek, R.J., Kak, A.C.,
A Knowledge Based Robotic Vision System,
CAIA84(45-50). BibRef 8400

Matsuyama, T.,
Knowledge Organization and Control Structure in Image Understanding,
ICPR84(1118-1127). BibRef 8400

Tanimoto, S.L.,
Paradigms for Control of Vision Using Inference in Networks,
CVWS82(3-13). BibRef 8200

Ogawa, H., Kurioka, S., Kitahashi, T., Tanaka, K.,
An Application of Knowledge Base for Image Analysis,
ICPR80(340-342). BibRef 8000

Dunlavey, M.R.,
An Hypothesis-Driven Vision System,
IJCAI75(616-619). BibRef 7500

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Knowledge-Based Vision, Surveys, Overviews .


Last update:Mar 16, 2024 at 20:36:19