Strat, T.M., and
Fischler, M.A.,
Context-Based Vision:
Recognizing Objects Using Information from Both 2-D and 3-D Imagery,
PAMI(13), No. 10, October 1991, pp. 1050-1065.
IEEE Abstract. IEEE Top Reference.
WWW Version.
System: Condor.
BibRef
9110
Earlier:
A Context-Based Recognition System for Natural Scenes and
Complex Domains,
DARPA90(456-472).
BibRef
Earlier: A2, A1:
Recognizing Objects in a Natural Environment:
A Contextual Vision System,
DARPA89(774-796).
BibRef
And:
Context-Based Vision: Recognition of Natural Scenes,
Asilomar89(532-536).
System: CVS.
Recognition, Context Based. This discusses the current SRI high-level vision effort. Addresses:
object recognition without accurate object delineation, use of
contest, use of geometry, and control of complexity. Uses context
sets and cliques.
BibRef
Strat, T.M.,
Decision Analysis Using Belief Functions,
ApproximateR(4), No. 5, September, 1990, pp. 391-418.
BibRef
9009
And: in Advances in the Dempster-Shafer Theory of Evidence,
ed. by R. Yager, M. Fedrizzi, and J. Kacprzyk, John Wiley & sons,
New York, 1994, pp. 275-310.
See also Mathematical Theory of Evidence, A.
BibRef
Strat, T.M.,
Explaining Evidential Analyses,
ApproximateR(3), No. 4, July 1989, pp. 299-353.
BibRef
8907
Strat, T.M.,
Natural Object Recognition,
New York:
Springer1992, 165pp.
ISBN 0-387-97832-1.
BibRef
9200
And:
STAN-CS-91-1376, Stanford, CA, December 1990.
BibRef
Ph.D.Thesis.
System: Condor.
Rule Based Analysis. The
BibRef
Bookfrom his thesis on general object recognition using
contextual cues. A set of processes interact through shared data structures.
Each process has an associated context set, that when satisfied causes
the process to run.
BibRef
Strat, T.M.,
Photogrammetry and Knowledge Representation in Computer Vision,
ISPRS94Symposium on Spatial Information from Digital
Photogrammetry and Computer Vision, Munich, September 1994.
BibRef
9409
Strat, T.M.,
Fischler, M.A.,
Natural Object Recognition:
A Theoretical Framework and Its Implementation,
IJCAI91(1264-1270).
BibRef
9100
Strat, T.M.[Thomas M.],
Fischler, M.A.[Martin A.],
The Use of Context in Vision,
Context95(xx)
BibRef
9500
Strat, T.M.[Thomas M.],
Fua, P.V.,
Connolly, C.I.,
Context-Based Vision,
Radius97(373-388).
BibRef
9700
Smith, G.B.,
Strat, T.M.,
Information Management in a Sensor-Based Autonomous System,
DARPA87(170-177).
BibRef
8700
Strat, T.M.,
Smith, G.B.,
Core Knowledge System:
Storage and Retrieval of Inconsistent Information,
DARPA88(660-665).
BibRef
8800
Strat, T.M.,
Using Context to Control Computer Vision Algorithms,
Ascona95(3-12).
BibRef
9500
Earlier:
Employing Contextual Information in Computer Vision,
DARPA93(217-229).
System: Condor. The use of context in understanding objects.
Describes the Prolog-like language used to control algorithms
in RCDE
BibRef
Strat, T.M.,
Smith, G.B.,
The Management of Spatial Information in a Mobile Robot,
SPMSF87(240-249).
BibRef
8700
Lowrance, J.,
Strat, T.M.,
Wesley, L.P.,
Garvey, T.D., and
Ruspini, E.,
The Theory, Implementation, and Practice of Evidential Reasoning,
Final Report,
SRIProject 5701, June 1991.
BibRef
9106
Lowrance, J.,
Ruspini, E., and
Strat, T.M.,
Understanding Evidential Reasoning,
SRI-TN-501, January 1991.
BibRef
9101
Bell, B.,
Pau, L.F.,
Context Knowledge and Search Control Issues in
Object-Oriented Prolog-Based Image Understanding,
PRL(13), 1992, pp. 279-290.
BibRef
9200
Pau, L.F.,
Context Related Issues in Image Understanding,
HPRCV97(Chapter IV:3).
(Digital Equipment Europe)
BibRef
9700
Liedtke, C.E.,
Bückner, J.,
Pahl, M.,
Stahlhut, O.,
Knowledge Based System for the Interpretation of Complex Scenes,
Ascona01(3-12).
Combine various features for roads and buildings.
0201
BibRef
Bückner, J.,
Pahl, M.,
Stahlhut, O.,
Liedtke, C.E.,
A Knowledge-Based System for Context Dependent Evaluation of Remote
Sensing Data,
DAGM02(58 ff.).
HTML Version.
0303
BibRef
Bückner, J.[Jürgen],
Pahl, M.[Martin],
Stahlhut, O.[Oliver],
Semantic Interpretation of Remote Sensing Data,
PCV02(A: 62).
0305
BibRef
Vailaya, A.[Aditya],
Zhang, H.J.[Hong-Jiang],
Yang, C.J.[Chang-Jiang],
Liu, F.I.[Feng-I],
Jain, A.K.[Anil K.],
Automatic image orientation detection,
IP(11), No. 7, July 2002, pp. 746-755.
WWW Version.
0207
BibRef
Earlier: A1, A2, A5 Only:
ICIP99(II:600-604).
IEEE Abstract. IEEE Top Reference. Find the orientation of the natural image using features.
BibRef
Zhou, G.D.[Guo-Dong],
Direct modelling of output context dependence in discriminative hidden
Markov model,
PRL(26), No. 5, April 2005, pp. 545-553.
WWW Version.
0501
BibRef
Luo, J.B.[Jie-Bo],
Boutell, M.R.[Matthew R.],
Automatic Image Orientation Detection via Confidence-Based Integration
of Low-Level and Semantic Cues,
PAMI(27), No. 5, May 2005, pp. 715-726.
IEEE Abstract. IEEE Top Reference.
0501
BibRef
Earlier:
A Probabilistic Approach to Image Orientation Detection via
Confidence-Based Integration of Low-Level and Semantic Cues,
MMDE04(141).
WWW Version.
0406How to display random collections of (consumer) images in the correct
orientation.
Low level cues are not sufficient.
BibRef
Boutell, M.R.[Matthew R.],
Luo, J.B.[Jie-Bo],
Bayesian fusion of camera metadata cues in semantic scene
classification,
CVPR04(II: 623-630).
IEEE Abstract. IEEE Top Reference.
0408Use camera metadata to aid classification (e.g. exposure time).
BibRef
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Model Selection for Unsupervised Learning of Visual Context,
IJCV(69), No. 2, August 2006, pp. 181-201.
WWW Version.
0606Choosing the model for learning.
Bayesian Information Criterion. (small data sets)
Completed Likelihood Akaike's Information Criterion. (otherwise)
BibRef
Wolf, L.[Lior],
Bileschi, S.M.[Stanley M.],
A Critical View of Context,
IJCV(69), No. 2, August 2006, pp. 251-261.
WWW Version.
0606Use context to select locations likely to contain particular objects.
BibRef
Wolf, L.[Lior],
Bileschi, S.M.[Stan M.],
Meyers, E.[Ethan],
Perception Strategies in Hierarchical Vision Systems,
CVPR06(II: 2153-2160).
WWW Version.
0606
BibRef
Bileschi, S.M.[Stanley M.],
StreetScenes: Towards Scene Understanding in Still Images,
Ph.D.Thesis, May 2006, MIT.
PDF Version.
BibRef
0605
Bileschi, S.M.[Stanley M.],
CBCL StreetScenes Challenge Framework,
Online2007.
WWW Version.
Dataset, Object Detection. Primarily for Cars, people, and street scenes.
Data is labeled.
BibRef
0700
Hoiem, D.[Derek],
Efros, A.A.[Alexei A.],
Hebert, M.[Martial],
Recovering Surface Layout from an Image,
IJCV(75), No. 1, October 2007, pp. 151-172.
WWW Version.
0709
BibRef
Earlier:
Putting Objects in Perspective,
CVPR06(II: 2137-2144).
WWW Version.
0606
BibRef
Earlier:
Geometric Context from a Single Image,
ICCV05(I: 654-661).
WWW Version.
0510Kanade issue.
Coarse properties (ground plane, sky, planar regions) from one
image.
Probabilistic approach to estimate 3D geometry so that not every
possible view is needed.
BibRef
Quickly determine the approximate surface structure from variety of cues.
Hoiem, D.[Derek],
Seeing the World Behind the Image:
Spatial Layout for 3D Scene Understanding,
CMU-RI-TR-07-28, August, 2007.
BibRef
0708
Ph.D.Thesis.
WWW Version.
BibRef
Hoiem, D.[Derek],
Rother, C.[Carsten],
Winn, J.[John],
3D Layout CRF for Multi-View Object Class Recognition and Segmentation,
CVPR07(1-8).
WWW Version.
0706
BibRef
Hoiem, D.[Derek],
Stein, A.N.[Andrew N.],
Efros, A.A.[Alexei A.],
Hebert, M.[Martial],
Recovering Occlusion Boundaries from a Single Image,
ICCV07(1-8).
WWW Version.
0710
BibRef
Bauckhage, C.,
Wachsmuth, S.,
Hanheide, M.,
Wrede, S.,
Sagerer, G.F.,
Heidemann, G.,
Ritter, H.,
The visual active memory perspective on integrated recognition systems,
IVC(26), No. 1, 1 January 2008, pp. 5-14.
WWW Version.
0711Cognitive vision; Contextual reasoning; Fusion; Architecture;
System integration
BibRef
Carbonetto, P.[Peter],
Dorkó, G.[Gyuri],
Schmid, C.[Cordelia],
Kück, H.[Hendrik],
de Freitas, N.[Nando],
Learning to Recognize Objects with Little Supervision,
IJCV(77), No. 1-3, May 2008, pp. 219-237.
WWW Version.
0803
BibRef
Earlier:
A Semi-supervised Learning Approach to Object Recognition with Spatial
Integration of Local Features and Segmentation Cues,
CLOR06(277-300).
WWW Version.
0711
BibRef
Carbonetto, P.[Peter],
de Freitas, N.[Nando],
Barnard, K.[Kobus],
A Statistical Model for General Contextual Object Recognition,
ECCV04(Vol I: 350-362).
WWW Version.
0405Given the image and captions (or descriptions)
learn the spatial relationships.
BibRef
Kück, H.[Hendrik],
Carbonetto, P.[Peter],
de Freitas, N.[Nando],
A Constrained Semi-supervised Learning Approach to Data Association,
ECCV04(Vol III: 1-12).
WWW Version.
0405Show how a wide class of data association tasks arising in computer
vision can be interpreted as a constrained semi-supervised learning
problem.
BibRef
Kumar, S.[Sanjiv],
Hebert, M.[Martial],
A Hierarchical Field Framework for Unified Context-Based Classification,
ICCV05(II: 1284-1291).
WWW Version.
0510
BibRef
Kumar, S.[Sanjiv],
Models for Learning Spatial Interactions in Natural Images for
Context-Based Classification,
CMU-CS-05-28, Robotics Institute, August, 2005.
WWW Version.
BibRef
0508
Morgenstern, C.[Christian],
Heisele, B.[Bernd],
Component based recognition of objects in an office environment,
MIT AIM-2003-024, November 28, 2003.
WWW Version.
0501
BibRef
Schlecht, J.[Joseph],
Barnard, K.[Kobus],
Pryor, B.[Barry],
Statistical Inference of Biological Structure and Point Spread
Functions in 3D Microscopy,
3DPVT06(373-380).
WWW Version.
0606
BibRef
Louie, J.[Jennifer],
A Biological Model of Object Recognition with Feature Learning,
MIT AI-TR-2003-009, May 28, 2003.
BibRef
0305
Ph.D.Thesis. 2003.
WWW Version. This thesis
presents a new model that integrates learning of object-specific features with the HMAX of Riesenhuber and Poggio
0306
BibRef
Serre, T.[Thomas],
Learning a Dictionary of Shape-Components in Visual Cortex:
Comparison with Neurons, Humans and Machines,
CSAIL-2006-028, April 2006.
WWW Version.
BibRef
0604
Serre, T.[Thomas],
Wolf, L.[Lior],
Poggio, T.[Tomaso],
A new biologically motivated framework for robust object recognition,
MIT AIM-2004-026, November 14, 2004.
WWW Version.
0501
BibRef
Serre, T.[Thomas],
Riesenhuber, M.[Maximilian],
Louie, J.[Jennifer],
Poggio, T.[Tomaso],
On the Role of Object-Specific Features for Real World Object
Recognition in Biological Vision,
BMCV02(387 ff.).
HTML Version.
0303
See also Robust Object Recognition with Cortex-Like Mechanisms.
BibRef
Pinhanez, C.[Claudio],
Bobick, A.F.[Aaron F.],
Using Approximate Models as Source of Contextual Information
for Vision Processing,
Context95(xx)
BibRef
9500
Hild, M., and
Shirai, Y.,
Interpretation of Natural Scenes Using Multi-Parameter Default
Models and Qualitative Constraints,
ICCV93(497-501).
WWW Version. Looks like a basic recognition scheme like early Ohta work
and UMass work.
BibRef
9300
Kadono, K.,
Asada, M.,
Shirai, Y.,
Context-Constrained Matching of Hierarchical CAD-Based Models for
Outdoor Scene Interpretation,
CADBV91(186-195).
BibRef
9100
Hild, M.,
Shirai, Y.,
Asada, M.,
Initial Segmentation For Knowledge Indexing,
ICPR92(I:587-590).
WWW Version.
BibRef
9200
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Context Supplied by Text or Language .