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
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PR(1), No. 3, March 1969, pp. 219-232.
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Earlier:
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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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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.,
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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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And: (Knowledge of...) ICPR82(654-669). BibRef

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Chen, S.,
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And: ASR-I90(Ch. 4). BibRef
And:
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Earlier:
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WWW Link. Interpretation in Prolog. Trigger C coded image processing. BibRef 9112

Ellis, T.J., Rosin, P.L., and Golton, P.,
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Lee, C.M., Pong, T.C., Slagle, J.R.,
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Meisels, A.,
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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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Eklundh, J.O.,
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Wallace, A.M.[Andrew M.],
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Grenander, U.[Ulf], Miller, M.I.,
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Aviad, Z., Lozinskii, E.,
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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.
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Earlier:
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VI96(49-56).
PS File. BibRef
Earlier:
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BMVC96(Poster Session 1). 9608
Optimization technique with feedback. University of Surrey BibRef

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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,
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Roli, F., Serpico, S.B., Vernazza, G.,
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Dellepiane, S.G., Venturi, G., Vernazza, G.L.,
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Dellepiane, S.G., Serpico, S.B., Vernazza, G.L.,
Analysis and Classification of SAR Images by a Knowledge-Based Approach,
ICPR88(II: 1207-1209).
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Kuruppu, N.R.,
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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.
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Chan, S.W.K., Leung, K.S., Wong, W.S.F.,
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Moody, J.[John], Flynn, P.J.[Patrick J.], Cohn, D.L.[David L.],
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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],
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Earlier: CVS99(522 ff.).
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Scene interpretation; Description logics; High-level vision BibRef

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Treiber, M.A.[Marco Alexander],
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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,
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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
Computer vision; 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
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Yu, L., Xie, J., Chen, S.,
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Maji, S.[Subhransu], Berg, A.C.[Alexander C.], Malik, J.[Jitendra],
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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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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],
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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.,
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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?,
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Scene analysis BibRef

Xie, Y.R.[Yu-Rui], Wu, Q.B.[Qing-Bo], Luo, B.[Bing], Huang, C.[Chao], Tang, L.Z.[Liang-Zhi],
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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],
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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],
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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
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Earlier:
Hierarchical Space Tiling for Scene Modeling,
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Springer DOI 1304
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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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Vision and language. Vision is part of an intelligent system that reasons, not just vision by itself. BibRef

Guo, R.Q.[Rui-Qi], Hoiem, D.[Derek],
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Earlier:
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ECCV12(V: 761-774).
Springer DOI 1210
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Lindner, A.[Albrecht], Susstrunk, S.,
Semantic-Improved Color Imaging Applications: It Is All About Context,
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IEEE DOI 1505
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Lindner, A.[Albrecht],
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Ph.D.. Thesis. BibRef

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
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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],
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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,
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IEEE DOI 1603
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Vedantam, R.[Ramakrishna], Lin, X.[Xiao], Batra, T.[Tanmay], Zitnick, C.L.[C. Lawrence], Parikh, D.[Devi],
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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],
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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],
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IEEE DOI 1609
image recognition BibRef

Gao, J., Zhang, T.Z.[Tian-Zhu], Yang, X.S.[Xiao-Shan], Xu, C.S.[Chang-Sheng],
Deep Relative Tracking,
IP(26), No. 4, April 2017, pp. 1845-1858.
IEEE DOI 1704
Machine learning BibRef

Malik, J.[Jitendra], Arbeláez, P.[Pablo], Carreira, J.[Joăo], Fragkiadaki, K.[Katerina], Girshick, R.[Ross], Gkioxari, G.[Georgia], Gupta, S.[Saurabh], Hariharan, B.[Bharath], Kar, A.[Abhishek], Tulsiani, S.[Shubham],
The three R's of computer vision: Recognition, reconstruction and reorganization,
PRL(72), No. 1, 2016, pp. 4-14.
Elsevier DOI 1604
Object recognition BibRef

Gori, M.[Marco], Lippi, M.[Marco], Maggini, M.[Marco], Melacci, S.[Stefano],
Semantic video labeling by developmental visual agents,
CVIU(146), No. 1, 2016, pp. 9-26.
Elsevier DOI 1604
Learning from constraints Developmental Visual Agents are life-long learning systems for video understanding. Go from unsupervised feature extraction to symbolic representations. BibRef

Thomas, S.S.[Sinnu Susan], Gupta, S.[Sumana], Subramanian, V.K.[Venkatesh K.],
Perceptual synoptic view-based video retrieval using metadata,
SIViP(11), No. 3, March 2017, pp. 549-555.
WWW Link. 1702
BibRef
Earlier:
Perceptual synoptic view of pixel, object and semantic based attributes of video,
JVCIR(38), No. 1, 2016, pp. 367-377.
Elsevier DOI 1605
Surveillance. Synopsis. Different levels of representation. BibRef

Donatti, G.S.[Guillermo Sebastián],
Memory Organization for Invariant Object Recognition and Categorization,
ELCVIA(15), No. 2, 2016, pp. 33-36.
DOI Link 1611
BibRef

Fan, M.[Miao], Zhou, Q.A.[Qi-Ang], Zheng, T.F.[Thomas Fang], Grishman, R.[Ralph],
Distributed representation learning for knowledge graphs with entity descriptions,
PRL(93), No. 1, 2017, pp. 31-37.
Elsevier DOI 1706
Knowledge, graph BibRef


Ali, A.R.[Afsheen Rafaqat], Shahid, U.[Usman], Ali, M.[Mohsen], Ho, J.[Jeffrey],
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

de Souza, F.D.M.[Fillipe D. M.], Sarkar, S.[Sudeep], Cámara-Chávez, G.[Guillermo],
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

Schwarz, K.[Katharina], Berg, T.L.[Tamara L.], Lensch, H.P.A.[Hendrik P. A.],
Auto-Illustrating Poems and Songs with Style,
ACCV16(IV: 87-103).
Springer DOI 1704
Large image dataset for selection. BibRef

Mottaghi, R.[Roozbeh], Hajishirzi, H.[Hannaneh], Farhadi, A.[Ali],
A Task-Oriented Approach for Cost-Sensitive Recognition,
CVPR16(2203-2211)
IEEE DOI 1612
BibRef

Ionescu, R.T.[Radu Tudor], Alexe, B.[Bogdan], Leordeanu, M.[Marius], Popescu, M.[Marius], Papadopoulos, D.P.[Dim P.], Ferrari, V.[Vittorio],
How Hard Can It Be? Estimating the Difficulty of Visual Search in an Image,
CVPR16(2157-2166)
IEEE DOI 1612
Human response time data. BibRef

Wu, Q.[Qi], Shen, C.H.[Chun-Hua], Liu, L.Q.[Ling-Qiao], Dick, A.[Anthony], van den Hengel, A.J.[Anton J.],
What Value Do Explicit High Level Concepts Have in Vision to Language Problems?,
CVPR16(203-212)
IEEE DOI 1612
Vision to language. BibRef

Mao, J.H.[Jun-Hua], Huang, J.[Jonathan], Toshev, A.[Alexander], Camburu, O.[Oana], Yuille, A.L.[Alan L.], Murphy, K.[Kevin],
Generation and Comprehension of Unambiguous Object Descriptions,
CVPR16(11-20)
IEEE DOI 1612
BibRef

Lu, C.[Cewu], Krishna, R.[Ranjay], Bernstein, M.[Michael], Fei-Fei, L.[Li],
Visual Relationship Detection with Language Priors,
ECCV16(I: 852-869).
Springer DOI 1611
Relationships identify objects. BibRef

Yu, L.C.[Li-Cheng], Poirson, P.[Patrick], Yang, S.[Shan], Berg, A.C.[Alexander C.], Berg, T.L.[Tamara L.],
Modeling Context in Referring Expressions,
ECCV16(II: 69-85).
Springer DOI 1611
How to refer to objects. BibRef

Mbock, E.A.M.[Etienne Aubin Mbe],
Image reconstruction using the reconfiguration technique,
AIPR15(1-9)
IEEE DOI 1605
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

de Lima, G.V.L.[Geovana V. L.], Castilho, T.R.[Thullyo R.], Bugatti, P.H.[Pedro H.], Saito, P.T.M.[Priscila T.M.], Lopes, F.M.[Fabrício M.],
A Complex Network-Based Approach to the Analysis and Classification of Images,
CIARP15(322-330).
Springer DOI 1511
Knowledge from multiple areas. BibRef

Savva, M.[Manolis], Chang, A.X.[Angel X.], Hanrahan, P.[Pat],
Semantically-enriched 3D models for common-sense knowledge,
Cognition15(24-31)
IEEE DOI 1510
Computational modeling. Physical properties connect to 3D models. BibRef

Zhu, Y.X.[Yi-Xin], Zhao, Y.B.[Yi-Biao], Zhu, S.C.[Song-Chun],
Understanding tools: Task-oriented object modeling, learning and recognition,
CVPR15(2855-2864)
IEEE DOI 1510
Tools such as hammer or brush. BibRef

Santos-Saavedra, D., Pardo, X.M., Iglesias, R., Canedo-Rodríguez, A., Álvarez-Santos, V.,
Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics,
IbPRIA15(130-137).
Springer DOI 1506
combination of an holistic representation and local information. BibRef

Chantas, G.[Giannis], Kitsikidis, A.[Alexandros], Nikolopoulos, S.[Spiros], Dimitropoulos, K.[Kosmas], Douka, S.[Stella], Kompatsiaris, I.[Ioannis], Grammalidis, N.[Nikos],
Multi-Entity Bayesian Networks for Knowledge-Driven Analysis of ICH Content,
CVONT14(355-369).
Springer DOI 1504
Intangible Cultural Heritage BibRef

Kadar, I.[Ilan], Ben-Shahar, O.[Ohad],
SceneNet: A Perceptual Ontology for Scene Understanding,
CVONT14(385-400).
Springer DOI 1504
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Tasli, H.E.[H. Emrah], Sicre, R.[Ronan], Gevers, T.[Theo], Alatan, A.A.[A. Aydin],
Geometry-constrained spatial pyramid adaptation for image classification,
ICIP14(1051-1055)
IEEE DOI 1502
Color BibRef

Khosla, A.[Aditya], An, B.[Byoungkwon], Lim, J.J.[Joseph J.], Torralba, A.[Antonio],
Looking Beyond the Visible Scene,
CVPR14(3710-3717)
IEEE DOI 1409
Analyze the environment in the urban scene, crime, what may be near, etc. BibRef

Divvala, S.K.[Santosh K.], Farhadi, A.[Ali], Guestrin, C.[Carlos],
Learning Everything about Anything: Webly-Supervised Visual Concept Learning,
CVPR14(3270-3277)
IEEE DOI 1409
BibRef

Ordonez, V.[Vicente], Berg, T.L.[Tamara L.],
Learning High-Level Judgments of Urban Perception,
ECCV14(VI: 494-510).
Springer DOI 1408
urban perception judgments for wealth, uniqueness, and safety. BibRef

Martinez-Enriquez, A.M., Escalada-Imaz, G., Muhammad, A.[Aslam],
Problem Solving Environment Based on Knowledge Based System Principles,
MCPR14(81-91).
Springer DOI 1407
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Chen, Z.C.[Zi-Chong], Yang, F.[Feng], Lindner, A.[Albrecht], Barrenetxea, G.[Guillermo], Vetterli, M.[Martin],
How is the weather: Automatic inference from images,
ICIP12(1853-1856).
IEEE DOI 1302
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Steinberg, D.M.[Daniel M.], Pizarro, O.[Oscar], Williams, S.B.[Stefan B.],
Synergistic Clustering of Image and Segment Descriptors for Unsupervised Scene Understanding,
ICCV13(3463-3470)
IEEE DOI 1403
Scene understanding BibRef

Saleh, B.[Babak], Farhadi, A.[Ali], Elgammal, A.M.[Ahmed M.],
Object-Centric Anomaly Detection by Attribute-Based Reasoning,
CVPR13(787-794)
IEEE DOI 1309
In an image, not actions. BibRef

Juneja, M.[Mayank], Vedaldi, A.[Andrea], Jawahar, C.V., Zisserman, A.[Andrew],
Blocks That Shout: Distinctive Parts for Scene Classification,
CVPR13(923-930)
IEEE DOI 1309
Scene Classification BibRef

Chen, J.J.[Jing-Jing], Cao, X.C.[Xiao-Chun], Zhang, B.[Bao],
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ICPR12(2829-2832).
WWW Link. 1302
BibRef

Fornoni, M.[Marco], Caputo, B.[Barbara],
Scene Recognition with Naive Bayes Non-linear Learning,
ICPR14(3404-3409)
IEEE DOI 1412
BibRef
Earlier:
Indoor Scene Recognition using Task and Saliency-driven Feature Pooling,
BMVC12(98).
DOI Link 1301
Feature extraction BibRef

Liu, Y.X.[Yi-Xian], Hao, P.W.[Peng-Wei], Izquierdo, E.[Ebroul],
Stage-based 3D scene reconstruction from single image,
ICPR12(1034-1037).
WWW Link. 1302
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Earlier:
Scene geometric recognition from monocular image,
3DTV12(1-4).
IEEE DOI 1212
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Jiang, Y.N.[Yu-Ning], Yuan, J.S.[Jun-Song], Yu, G.[Gang],
Randomized Spatial Partition for Scene Recognition,
ECCV12(II: 730-743).
Springer DOI 1210
how to use spatial info BibRef

Ji, C.J.[Chuan-Jun], Zhou, X.D.[Xiang-Dong], Lin, L.[Lan], Yang, W.D.[Wei-Dong],
Labeling Images by Integrating Sparse Multiple Distance Learning and Semantic Context Modeling,
ECCV12(IV: 688-701).
Springer DOI 1210
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Kwitt, R.[Roland], Vasconcelos, N.M.[Nuno M.], Rasiwasia, N.[Nikhil],
Scene Recognition on the Semantic Manifold,
ECCV12(IV: 359-372).
Springer DOI 1210
Scene category. BibRef

Redi, M.[Miriam], Merialdo, B.[Bernard],
Enhancing Semantic Features with Compositional Analysis for Scene Recognition,
Concept12(III: 446-455).
Springer DOI 1210
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Parizi, S.N.[Sobhan Naderi], Oberlin, J.G.[John G.], Felzenszwalb, P.F.[Pedro F.],
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CVPR12(2775-2782).
IEEE DOI 1208
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Yu, X.D.[Xiao-Dong], Fermuller, C.[Cornelia], Teo, C.L.[Ching Lik], Yang, Y.Z.[Ye-Zhou], Aloimonos, Y.[Yiannis],
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ICCV11(810-817).
IEEE DOI 1201
Use high-level knowledge for recognition. BibRef

Möller, B.[Birgit], Greß, O.[Oliver], Posch, S.[Stefan],
Knowing What Happened: Automatic Documentation of Image Analysis Processes,
CVS11(1-10).
Springer DOI 1109
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Sherrah, J.[Jamie],
Learning to Adapt: A Method for Automatic Tuning of Algorithm Parameters,
ACIVS10(I: 414-425).
Springer DOI 1012
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Kulikowski, J.L.[Juliusz L.],
Ontological Models as Tools for Image Content Understanding,
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.],
Seeing People in Social Context: Recognizing People and Social Relationships,
ECCV10(V: 169-182).
Springer DOI 1009
Familial social relationships to recognize people, and to recognize such relationships from image. BibRef

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],
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CVPR11(1961-1968).
IEEE DOI 1106
BibRef

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
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Gao, T.S.[Tian-Shi], Koller, D.[Daphne],
Discriminative learning of relaxed hierarchy for large-scale visual recognition,
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
BibRef

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],
Statistics of 3D object locations in images,
CMU-RI-TR-08-43, October, 2008.
WWW Link. BibRef 0810

Wojek, C.[Christian], Schiele, B.[Bernt],
A Dynamic Conditional Random Field Model for Joint Labeling of Object and Scene Classes,
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
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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,
CRV06(9-9).
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:
IEEE DOI 0606
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
BibRef

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
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Weber, M., Welling, M., Perona, P.,
Towards Automatic Discovery of Object Categories,
CVPR00(II: 101-108).
IEEE DOI 0005
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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
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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
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Oshitani, T.[Tohru], Watanabe, T.[Toyohide],
Parallel Map Recognition Based on Multilayer Partitioned Blackboard Model,
ICPR98(Vol II: 1604-1606).
IEEE DOI 9808
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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
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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,
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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:Sep 25, 2017 at 16:36:46