There are many great courses and sites now with good lists of papers as well as extensive links to code and data. Good sites include
Grauman and Liebe, AAAI'08 Tutorial
* Object Recognition in the Geometric Era: A Retrospective
Joseph L. Mundy [pdf]* The Evolution of Object Categorization and the Challenge of Image Abstraction
Sven Dickinson [pdf]Historical perspective (highly recommended but not required):
Representation and Recognition of the Spatial Organization of Three-Dimensional. Shapes. D. Marr; H. K. Nishihara. Proceedings of the Royal Society of London. Series B, Biological Sciences, Vol. 200, No. 1140.
(Feb. 23, 1978), pp. 269-294 [pdf]Extra historical perspective (not required):
Model-based three-dimensional interpretations of two-dimensional images, Rodney A. Brooks
IEEE Transactions on Pattern Analysis and Machine Intelligence (1983) (Acronym [pdf])
* A Fast Data Collection and Augmentation Procedure for Object Recognition, Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. In AAAI, 2008. [pdf] [web]
Background (not required):
Dataset issues in object recognition.
J. Ponce, T. L. Berg, M. Everingham, D. A. Forsyth, M. Hebert,
S. Lazebnik, M. Marszalek, C. Schmid, B. C. Russell, A. Torralba,
C. K. I.Williams, J. Zhang, and A. Zisserman. In Toward Category-Level Object Recognition, pages 29–
48, 2006. [pdf]Alexander Sorokin and David Forsyth, "Utility data annotation with Amazon Mechanical Turk", CVPR 2008 [pdf] [web]
Fei-Fei/Fergus/Torralba slides on datasets [ppt]
80 million tiny images [interactive website]
* D. Lowe. Distinctive image features from scale-invariant keypoints.
International Journal of Computer Vision, 60(2):91–110, 2004. [pdf] [code]D. Lowe. Three-dimensional object recognition from single two-dimensional
images. Artificial Intelligence, 31:355–395, 1987. [pdf]
* Histograms of Oriented Gradients for Human Detection, by N.Dalal, B.Triggs. CVPR 2005 [pdf] [demo video] [software] [PASCAL datasets] [Dalal code] [PHOG code]
The PASCAL site and summaries at recent workshops give a snapshot of the field and current methods.
Fergus, R. , Perona, P. and Zisserman, A., "Object Class Recognition by Unsupervised Scale-Invariant Learning", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2003) [pdf]
J. Sivic and A. Zisserman. Video Google: A Text Retrieval Approach to Object Matching in Videos. ICCV 2003. [pdf]
Discovering Object Categories in Image Collections. Josef Sivic, Bryan C. Russell, Alexei A. Efros,. Andrew Zisserman, William T. Freeman. [pdf]
Object Recognition using Multidimensional Receptive Field Histograms (ECCV 1996)
by Bernt Schiele, James L. Crowley [pdf]A Bayesian Hierarchical Model for Learning Natural Scene Categories
Li Fei-Fei, Pietro Perona, CVPR'05 [pdf]Object Class Segmentation using Random Forests
Schroff, F. , Criminisi, A. and Zisserman, A.
Proceedings of the British Machine Vision Conference (2008)
S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(4):509–522, 2002. [pdf] [web] [code]
Shape Matching and Object Recognition using Low Distortion Correspondences. Alexander C. Berg Tamara L. Berg Jitendra Malik, CVPR'05 [pdf]
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce, CVPR 2006 [pdf]Bastian Leibe, Ales Leonardis, and Bernt Schiele, "Combined Object Categorization and Segmentation with an Implicit Shape Model", In ECCV'04 Workshop on Statistical Learning in Computer Vision, Prague, May 2004. [pdf] [code] [video1] [video2]
Fidler and A. Leonardis. Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts. CVPR 2007. [pdf]
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision, Volume 14 , Issue 1 (January 1995)
Hiroshi Murase, Shree K. Nayar [pdf]Joerg Liebelt, Cordelia Schmid, Klaus Schertler, "Viewpoint-independent object class detection using 3d feature maps", CVPR 2008 [pdf]
Pingkun Yan, Saad M. Khan, and Mubarak Shah, 3D Model based Object Class Detection in An Arbitrary View, IEEE International Conference on Computer Vision (ICCV), 2007. [pdf]
A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, B. Schiele, and L. Van Gool. Towards multi-view object class detection. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2006. [pdf]
Michael Stark, Bernt Schiele, "How Good are Local Features for Classes of Geometric Objects", ICCV 2007 [pdf]
K. Mikolajczyk and C. Schmid, Scale and Affine invariant interest point detectors. In IJCV 1(60):63-86, 2004. [pdf]
Krystian Mikolajczyk, Tinne Tuytelaars, Cordelia Schmid, Andrew Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, L. Van Gool, A comparison of affine region detectors, IJCV - 2005
Krystian Mikolajczyk, Cordelia Schmid, A performance evaluation of local descriptors, PAMI - 2005
Michael Calonder, Vincent Lepetit, Pascal Fua, "Keypoint Signatures for Fast Learning and Recognition", ECCV 2008, http://cvlab.epfl.ch/~vlepetit/papers/calonder_eccv08.pdf
Efficient Image Matching with Distributions of Local Invariant Features
Kristen Grauman and Trevor Darrell, CVPR 2005 [pdf]Background:
Local Invariant Feature Detectors: A Survey, by T. Tuytelaars and K. Mikolajczyk. Foundations and Trends in Computer Graphics and Vision, 2008. [pdf] [code]
Multi-cue 3D object recognition in knowledge-based vision-guided humanoid robot system
Okada, K.; Kojima, M.; Tokutsu, S.; Maki, T.; Mori, Y.; Inaba, M.
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on
Volume , Issue , Oct. 29 2007-Nov. 2 2007 Page(s):3217 - 3222Robotic Grasping of Novel Objects, Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng. In NIPS 19, 2007. [pdf]
Michael Stark, Philipp Lies, Michael Zillich, Jeremy Wyatt and Bernt Schiele, "Functional Object Class Detection Based on Learned Affordance Cues", VCS 2008. http://www.mis.informatik.tu-darmstadt.de/People/stark/stark08icvs.pdf
Torralba, A., Murphy, K. and Freeman, W. Sharing Visual Features for Multiclass and Multiview Object Detection. PAMI 2007
Discovering object categories in image collections
Josef Sivic Bryan C. Russell Alexei A. Efros Andrew Zisserman William T. Freeman [pdf]L. Fei-Fei, R. Fergus, and P. Perona. One-shot learning of object
categories. IEEE Transactions on Pattern Analysis and Machine In-
telligence, 28(4):594–611, 2006.Unsupervised Learning of Categories from
Sets of Partially Matching Image Features
Kristen Grauman and Trevor Darrell, CVPR 2006 [pdf][2] M. Weber, M. Welling and P. Perona. Unsupervised Learning of Models for Recognition. In ECCV, 2000.
R. Fergus, P. Perona, and A. Zisserman. Weakly supervised scale-invariant
learning of models for visual recognition. International Journal of Computer Vision, 71(3):273–303, 2007.
[3] Paul Viola and Michael Jones, "Rapid object detection using a boosted cascade of simple features," Conference on Computer Vision and Pattern Recognition, 2001, pp. 511-518. [PDF]
Saad M. Khan, Pingkun Yan, and Mubarak Shah, A Homographic Framework for the Fusion of Multi-view Silhouettes, IEEE International Conference on Computer Vision (ICCV), 2007. [pdf]
Calibration
Ira. Light, shading.
---------------
lecun
hinton
Fua tracking WHAT PAPER?
Radu Rusu http://www9.cs.tum.edu/people/rusu/publications/ WHAT PAPER?
Geons
M. Pilu and R. B. Fisher. Recognition of geons by parametric deformable
contour models. In Proceedings, European Conference on
Computer Vision, pages 71–82, 1996.
http://classes.engr.oregonstate.edu/eecs/spring2006/cs559/papers.html
-----------------
http://www.cs.utexas.edu/~grauman/courses/spring2007/395T/schedule.htm
links to sift code etc.
P. Moreels and P. Perona. Evaluation of Features Detectors and Descriptors based on 3D objects. ICCV 2005
J. Sivic and A. Zisserman. Video Google: A Text Retrieval Approach to Object Matching in Videos. ICCV 2003.
G. Csurka, C. Bray, C. Dance, and L. Fan. Visual categorization with bags of keypoints. In Workshop on Statistical Learning in Computer Vision, ECCV, 2004.
F. Perronnin, C. Dance, G. Csurka, M. Bressan. Adapted Vocabularies for Generic Visual Categorization, ECCV 2006.
Moosmann, Triggs and Jurie. Fast Discriminative Visual Codebooks using Randomized Clustering Forests, NIPS 2006
J. Winn, A. Criminisi and T. Minka. Object categorization by learned universal visual dictionary. ICCV 2005.
S. Savarese, J. Winn, A. Criminisi. Discriminative Object Class Models of Appearance and Shape by Correlatons. CVPR 2006
M. Marszalek and C. Schmid. Spatial Weighting for Bag-of-Features. CVPR 2006.
S. Lazebnik, C. Schmid, and J. Ponce. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, CVPR 2006
Y. Lamdan, J.T. Schwartz, and H. Wolfson. Geometric hashing: A general and efficient model-based recognition scheme. ICCV 1988.
T. Sebastian, P. Klein, and B. Kimia: Recognition of Shapes by Editing Shock Graphs. ICCV 2001.
A. Thayananthan, B. Stenger, P. H. S. Torr, and R. Cipolla. Shape Context and Chamfer Matching in Cluttered Scenes. CVPR 2003.
T. Hertz, A. Bar-Hillel and D. Weinshall, Learning Distance Functions for Image Retrieval, CVPR 2004
A. Frome, Y. Singer, and J. Malik. Image Retrieval and Classification Using Local Distance Functions. NIPS 2006.
V. Athitsos and S. Sclaroff. Boosting Nearest Neighbor Classifiers for Multiclass Recognition. Workshop on Learning in CVPR 2005.
V. Athitsos and S. Sclaroff. Efficient Nearest Neighbor Classification Using a Cascade of Approximate Similarity Measures. CVPR 2005
D. Nister and H. Stewenius. Scalable Recognition with a Vocabulary Tree. CVPR 2006.
S. Obdrzalek and Jiri Matas. Sub-linear Indexing for Large Scale Object Recognition. BMVC 2005.
Murphy, Torralba & Freeman. Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes. NIPS 2003
D. Hoiem, A. Efros, and M. Hebert, Putting Objects in Perspective, CVPR 2006.
Sivic, J., Russell, B., Efros, A., Zisserman, A. and Freeman, W. Discovering Objects and their Location in Images. ICCV 2005
Russell, B. C. , Efros, A. A. , Sivic, J. , Freeman, W. T. and Zisserman, A. Using Multiple Segmentations to Discover Objects and their Extent in Image Collections. CVPR 2006
K. Grauman and T. Darrell. Unsupervised Learning of Categories from Sets of Partially Matching Image Features. CVPR 2006
(background) K. Grauman and T. Darrell. The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features. ICCV 2005
R. Fergus, L. Fei-Fei, P. Perona, and A. Zisserman. Learning Object Categories from Google’s Image Search. ICCV 2005.
L. Fei-Fei, R. Fergus, and P. Perona. A Bayesian approach to Unsupervised One-Shot learning of Object categories. ICCV 2003
E. Bart, S. Ullman. Cross-generalization: learning novel classes from a single example by feature replacement. CVPR, 2005.
Torralba, A., Murphy, K. and Freeman, W. Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection. CVPR 2004
A. Opelt, A. Pinz, and A. Zisserman. Incremental learning of object detectors using a visual shape alphabet. CVPR 2006.
-----------------
http://research.microsoft.com/en-us/um/people/larryz/objectrecognitionlist.htm
David G. Lowe, Local feature view clustering for 3D object recognition, IEEE Conference on Computer Vision and Pattern Recognition, 2001, pp. 682-688.
Recognition:
Sivic, J. and Zisserman,A., Video Google: A Text Retrieval Approach to Object Matching in Videos, ICCV (2003)
Y. Amit and D. Geman., A computational model for visual selection. Neural Computation, 11(7):1691-1715, 1999.
Pictorial structures for object recognition.
P. Felzenszwalb and D. Huttenlocher. CVPR, pages 2066-2073, 2000.
M. Burl, M.Weber, and P. Perona. , A probabilistic approach to object recognition using local photometry and global geometry. ECCV, pages 628-641, 1998.
----------
A cubist approach to object recognition
Nelson, R.C.; Selinger, A.
Computer Vision, 1998. Sixth International Conference on
Volume , Issue , 4-7 Jan 1998 Page(s):614 - 621
Digital Object Identifier 10.1109/ICCV.1998.710781
-------
http://www.nada.kth.se/cvap/internal/recog/recog.html
Discovering object categories in image collections , Technical Report A. I. Memo 2005-005, MIT, 2005
Efficient Image Matching with Distributions of Local Invariant Features , CVPR 2005
Unsupervised Learning of Categories from Sets of Partially Matching Image Features , CVPR 2006
Beyond Bags of Features - Spatial Pyramid Matching for Recognizing Natural Scene Categories, CVPR 2006
Discriminative Object Class Models of Appearance and Shape by Correlatons, CVPR 2006
Learning Hierarchical Models of Scenes, Objects, and Parts, ICCV 2005
Spatial Priors for Part-Based Recognition using Statistical Models, CVPR 2005
Hierarchical Part-Based Visual Object Categorization, CVPR 2005
Object Class Recognition by Unsupervised Scale-Invariant Learning, CVPR 2003
Combined object categorization and segmentation with an implicit shape model, SLCV 2004 (ECCV Workshop)
An Implicit Shape Model for Combined Object Categorization and Segmentation, LNCS 4170/2006 - "Toward Category-Level Object Recognition"
80 million tiny images - a large dataset for non-parametric object and scene recognition, PAMI 2008
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition, CVPR 2007
Image Classification using Random Forests and Ferns, ICCV 2007
A Boundary-Fragment-Model for Object Detection, ECCV 2006
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching, PAMI 2007
Human Detection Using Oriented Histograms of Flow and Appearance, ECCV 2006
Unsupervised Learning of Visual Taxonomies , CVPR 2008
Unsupervised Modeling of Object Categories Using Link Analysis Techniques , CVPR 2008
Similarity-based cross-layered hierarchical representation for object categorization , CVPR 2008
Sharing visual features for multiclass and multiview object detection , PAMI 2007
OBJCUT , CVPR 2005
TextonBoost - Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation , ECCV 2006
Robust Higher Order Potentials for Enforcing Label Consistency , CVPR 2008
Viewpoint-Independent Object Class Detection using 3D Feature Maps , CVPR 2008
3D LayoutCRF for Multi-View Object Class Recognition and Segmentation , CVPR 2007