CSC2523: Shape Perception in Human and Computer Vision

 

Instructor: Sven Dickinson

 

Each week, there will typically be 2 required readings, all available electronically on the secure course website (for copyright reasons – you’ll need the access password from the instructor); on one occasion, there will be three readings, including one very short one.  Supplemental readings are provided for those that are interested in learning more about a given topic; they are not required reading.

 

1. Introduction to Shape Perception

 

No required readings – instructor will provide overview of course and cover all administrative details.

 

Supplemental:

 

S. Dickinson and Z. Pizlo (Eds.), Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective”, Advances in Computer Vision and Pattern Recognition Series, Springer Verlag, 2013.

 

2. Perceptual Grouping: the Foundation of Shape Perception

 

A. Witkin and J. Tenenbaum, “On the role of structure in vision”, in Human and Machine Vision (J. Beck, B. Hope, and A. Rosenfeld, Eds.), pp 481–543, Academic Press, 1983.

http://www.cs.toronto.edu/~sven/2523/Papers/WitkinTenenbaum1983.pdf

 

Y. Qi, Y.-Z. Song, T. Xiang, H. Zhang, T. Hospedales, Y. Li, and J. Guo, “Making Better Use of Edges via Perceptual Grouping”, Proceedings, IEEE Conference on Computer Vision and Pattern Recognition, 2015.

http://www.cs.toronto.edu/~sven/2523/Papers/Qi2015.pdf

 

Supplemental:

 

F. Attneave, “Some Informational Aspects of Visual Perception”, Psychological Review, Volume 61, Number 3, 1954, pp 183-193.

http://www.cs.toronto.edu/~sven/2523/Papers/Attneave1954.pdf

 

J. Feldman, “Bayesian Contour Integration”, Perception and Psychophysics, Volume 63, Number 7, 2001, pp 1171-1182.

http://www.cs.toronto.edu/~sven/2523/Papers/feldman_bayes.pdf

 

J. Wagemans, J. Elder, M. Kubovy, S. Palmer, M. Peterson, M. Singh, and R. von der Heydt, “A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization”, Psychological Bulletin, Volume 138, Number 6, 2012, pp 1172-1217.

http://www.cs.toronto.edu/~sven/2523/Papers/WagemansGestalt1.pdf

 

J. Wagemans, J. Feldman, S. Gepshtein, R. Kimchi, J. Pomerantz, P. van der Helm, and C.

van Leeuwen, “A Century of Gestalt Psychology in Visual Perception: II. Conceptual and Theoretical Foundations”, Psychological Bulletin, Volume 138, Number 6, 2012, 1218-1252.

http://www.cs.toronto.edu/~sven/2523/Papers/WagemansGestalt2.pdf

 

K. Greff, A. Rasmus, M. Berglund, T. H. Hao, J. Schmidhuber, and H. Valpola, “Tagger: Deep unsupervised perceptual grouping”, Proceedings, Conference on Neural Information Processing Systems (NIPS), 2016.

http://www.cs.toronto.edu/~sven/2523/Papers/Greff2016.pdf

 

3. Separating the Shape from its Background: Contour Closure

 

J. Elder and S. Zucker, “The effect of contour closure on the rapid discrimination of two-dimensional shapes”, Vision Research, Volume 33, Number 7, 1993, pp 981-991.

http://www.cs.toronto.edu/~sven/2523/Papers/ElderZucker1993.pdf

 

A. Levinshtein, C. Sminchisescu, and S. Dickinson, “Optimal Image and Video Closure by Superpixel Grouping”, International Journal of Computer Vision, Volume 100, Number 1, 2012, pp 99-119.

http://www.cs.toronto.edu/~sven/Papers/IJCV-closure.pdf

 

Supplemental:

 

I. Kovacs and B. Julesz, “A closed curve is much more than an incomplete one: Effect of closure in figure-ground segmentation”, Proc. Natl. Acad. Sci. USA, Volume 90, 1993, pp 7495-7497.

http://www.cs.toronto.edu/~sven/2523/Papers/KovacsJulesz1993.pdf

 

P. Garrigan, “The effect of contour closure on shape recognition”, Perception, Volume 41, Number 2, 2012, pp 221-235.

http://www.cs.toronto.edu/~sven/2523/Papers/Garrigan2012.pdf

 

4. Object-Centered vs Viewer-Centered Shape Perception

 

R. Shephard and J. Metzler, “Mental Rotation of Three-Dimensional Objects”, Science, Volume 171, Number 3972, 1971, pp 701-703.

http://www.cs.toronto.edu/~sven/2523/Papers/ShepardMetzler71.pdf

 

S. Edelman and H. Bulthoff, “Orientation Dependence in the Recognition of Familiar and Novel Views of Three-Dimensional Objects”, Vision Research, Volume 32, Number 12, pp 2385-2400.

http://www.cs.toronto.edu/~sven/2523/Papers/EdelmanBulthoff92.pdf

 

Supplemental:

 

E. L. J. Leeuwenberg, “A Perceptual Coding Language for Visual and Auditory Patterns”, The American Journal of Psychology, Volume 84, Number 3, 1971, pp 307-349.

http://www.cs.toronto.edu/~sven/2523/Papers/Leeuwenberg1971.pdf

 

J. Koenderink and A. van Doorn, “The Singularities of the Visual Mapping”, Biological Cybernetics, Volume 24, 1976, pp 51-59.

http://www.cs.toronto.edu/~sven/2523/Papers/Koenderink1976.pdf

 

I. Rock and J. DiVita, “A Case of Viewer-Centered Object Perception”, Cognitive Psychology, Volume 19, 1987, pp 280-293.

http://www.cs.toronto.edu/~sven/2523/Papers/Rock_Divita_1987.pdf

 

M. Tarr and S. Pinker, “Mental rotation and orientation-dependence in shape recognition”, Cognitive Psychology, Volume 21, 1989, pp 233-282.

http://www.cs.toronto.edu/~sven/2523/Papers/TarrPinker1989.pdf

 

S. Ullman and R. Basri, “Recognition by linear combinations of models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 13, 1991, pp 992-1006.

http://www.cs.toronto.edu/~sven/2523/Papers/Basri91.pdf

 

S. Dickinson, A. Pentland, and A. Rosenfeld, “3-D Shape Recovery Using Distributed Aspect Matching”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 14, Number 2, 1992, pp 174 - 198.

http://www.cs.toronto.edu/~sven/Papers/pami-aspect.pdf


S. Dickinson, A. Pentland, and A. Rosenfeld, “From volumes to views: an approach to 3D object recognition”, CVGIP: Image Understanding, Volume 55, Number 2, 1992, pp 130-154.

http://www.cs.toronto.edu/~sven/Papers/cviu92.pdf

 

N. Logothetis, J. Pauls, and T. Poggio, Shape representation in the inferior temporal cortex of monkeys”, Current Biology, Volume 5, Number 5, 1995, pp 552-563.

http://www.cs.toronto.edu/~sven/2523/Papers/Logothetis1995.pdf

 

P. Sinha and T. Poggio, “Role of Learning in three-dimensional form perception”, Nature, Volume 384, 1996, pp 460-463.

http://www.cs.toronto.edu/~sven/2523/Papers/sinha_poggio_1996.pdf

 

Z. Pizlo and A. Stevenson, “Shape Constancy from Novel Views”, Perception & Psychophysics, 1999, 61 (7), pp 1299-1307.

http://www.cs.toronto.edu/~sven/2523/Papers/pizlo-stevenson-99.pdf

 

Y. Yamane, E. Carlson, K. Bowman, Z. Wang, and C. Connor, “A Neural Code for Three-Dimensional Object Shape in Macaque Inferotemporal Cortex”, Nature Neuroscience, Volume 11, Number 11, 2008, pp 1352-1360.

http://www.cs.toronto.edu/~sven/2523/Papers/Yamane2008.pdf

 

Z. Pizlo, T. Sawada, Y. Li, W. Kropatsch, and R. Steinman, “New approach to the perception of 3D shape based on veridicality, complexity, symmetry and volume”, Vision Research, Volume 50, 2010, pp 1-11.

http://www.cs.toronto.edu/~sven/2523/Papers/Pizlo2010.pdf

 

5. Polyhedral Shape Perception

 

M. Chan, A. Stevenson, Y. Li, and Z. Pizlo, “Binocular shape constancy from novel views: the role of a priori constraints”, Perception & Psychophysics, Volume 68, 2006, pp 1124-1139. 

http://www.cs.toronto.edu/~sven/2523/Papers/Pizlo2006.pdf

 

D. Lowe, “Three-Dimensional Object Recognition from Single Two-Dimensional Images, Artificial Intelligence, Volume 31, Number 3, 1987, pp 355-395.
http://www.cs.toronto.edu/~sven/2523/Papers/lowe.pdf

 

Supplemental:

 

L.G. Roberts, “Machine Perception of 3-D Solids” Optical and Electro-Optical Information Processing, (J. T. Tippet et al., Eds.), 1965, pp 159-197.

www.packet.cc/files/mach-per-3D-solids.html#*

http://www.cs.toronto.edu/~sven/2523/Papers/RobertsThesis1965.pdf (thesis)


D. Lowe, “The viewpoint consistency constraint”, International Journal of Computer Vision, Volume 1, Number 1, 1987, pp 57-72.

http://www.cs.toronto.edu/~sven/2523/Papers/lowe.pdf

 

D. Huttenlocher and S. Ullman, “Recognizing Solid Objects by Alignment with an Image”, International Journal of Computer Vision, Volume 5, Number 2, 1990, pp 195-212. http://www.cs.toronto.edu/~sven/2523/Papers/huttenlocher.pdf

 

6. Symmetry as a Basis for 2-D Shape Perception

 

(Note: the first paper is very short; therefore, one student will cover the first two, while the second student covers the third)

 

I. Kovacs and B. Julesz, “Perceptual Sensitivity Maps within Globally Defined Visual Shapes”, Nature, Volume 370, 1994, pp 644–646.

http://www.cs.toronto.edu/~sven/2523/Papers/KovacsJulesz94.pdf

 

J. Feldman and M. Singh, “Bayesian estimation of the shape skeleton”, Proceedings of the National Academy of Sciences, Volume 103, number 47, 2006, pp 18014-18019.

http://www.cs.toronto.edu/~sven/2523/Papers/feldman_singh_skeletons.pdf

 

A. Levinshtein, C. Sminchisescu, and S. Dickinson, “Multiscale Symmetric Part Detection and Grouping”, International Journal of Computer Vision, Volume 104, Number 2, 2013, pp 117-134.

http://www.cs.toronto.edu/~sven/2523/Papers/Levinshtein2013.pdf

 

Supplemental:

 

H. Blum, “Discussion Paper: A Geometry for Biology”, Annals of the New York Academy of Sciences, Volume 231, Number 1, 1974, pp 19-30.

http://www.cs.toronto.edu/~sven/2523/Papers/Blum1974.pdf

 

I. Kovacs, A. Feher, and B. Julesz, “Medial-point description of shape: A representation for action coding and its psychophysical correlates”, Vision Research, Volume 38, 1998, pp 2323-2333.

http://www.cs.toronto.edu/~sven/2523/Papers/KovacsFeherJulesz98.pdf

 

B. Kimia, “On the Role of Medial Geometry in Human Vision”, Journal of Physiology Paris, Volume 97, 2003, pp 155-190.

http://www.cs.toronto.edu/~sven/2523/Papers/KimiaPhysiology.pdf

 

H. Ling and D. Jacobs, “Shape Classification Using the Inner-Distance”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 29, Number 2, 2007, pp 286-299.

http://www.cs.toronto.edu/~sven/2523/Papers/LingJacobs2007.pdf

 

C.-C. Hung, E. Carlson, and C. E. Connor, “Medial Axis Shape Coding in Macaque Inferotemporal Cortex”, Neuron, Volume 74, 2012, pp 1099-1113.

http://www.cs.toronto.edu/~sven/2523/Papers/HungCarlsonConnor2012.pdf

 

M. Lescroart and I. Biederman, “Cortical Representation of Medial Axis Structure”, Cerebral Cortex, Volume 23, 2013, pp 629-637.

http://www.cs.toronto.edu/~sven/2523/Papers/Lescroart2013.pdf

 

C. Firestone and B. Scholl, “`Please Tap the Shape, Anywhere You Like’: Shape Skeletons in Human Vision Revealed by an Exceedingly Simple Measure”, Psychological Science, Volume 25, Number 2, 2014, pp 377–386.

http://www.cs.toronto.edu/~sven/2523/Papers/FirestoneScholl.pdf

 

7. Symmetry as a Basis for 3-D Shape Perception

 

D. Marr and H.K. Nishihara, “Representation and Recognition of the Spatial Organization of Three Dimensional Shapes”, Proceedings of Royal Society of London B, Volume 200, 1978, pp 269-294.
http://www.cs.toronto.edu/~sven/2523/Papers/MarrNishihara1978.pdf

 

R. Brooks, “Symbolic Reasoning Among 3-D Models and 2-D Images", Artificial Intelligence Journal, Volume 17, Numbers 1-3, 1981, pp 285-348.

http://www.cs.toronto.edu/~sven/2523/Papers/BrooksAIJ81.pdf

 

Supplemental:

 

T. Binford, “Visual Perception by Computer”, Proceedings, IEEE Conference on Systems and Control, Miami, FL, 1971.
http://www.cs.toronto.edu/~sven/2523/Papers/binford.pdf

 

G. Agin and T. Binford, “Computer Description of Curved Objects”, IEEE Transactions on Computers, Volume 25, Number 4, 1976, pp 439-449.
http://www.cs.toronto.edu/~sven/2523/Papers/AginBinford76.pdf

 

R. Nevatia and T. Binford, “Description and Recognition of Curved Objects”, Artificial Intelligence, Volume 8, 1977, pp 77-98.
http://www.cs.toronto.edu/~sven/2523/Papers/nevatia.pdf

 

M. Ovsjanikov, J. Sun, and L. Guibas, “Global Intrinsic Symmetries of Shapes”, Eurographics Symposium on Geometry Processing 2008, Volume 27, Number 5, 2008.

http://www.cs.toronto.edu/~sven/2523/Papers/ovs-symm.pdf

 

8. Qualitative Shape Perception in 2-D

 

W. Richards and D. Hoffman, “Codon constraints on closed 2D shapes”, Computer Vision, Graphics and Image Processing, Volume 31, Number 3, 1985, pp 265-281.

http://www.cs.toronto.edu/~sven/2523/Papers/RichardsHoffman1985.pdf

 

K. Siddiqi, A. Shokoufandeh, S. Dickinson, and S. Zucker, “Shock Graphs and Shape Matching”, International Journal of Computer Vision, Volume 30, 1999, pp 1-24.

http://www.cs.toronto.edu/~sven/2523/Papers/ShockGraph.pdf

 

Supplemental:

 

S. Belongie, J. Malik and J. Puzicha, ``Shape Matching and Object Recognition Using Shape Contexts, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 24, Number 4, pp 509-522, 2002.
http://www.cs.toronto.edu/~sven/2523/Papers/belongie.pdf

 

9. Qualitative Shape Perception in 3-D

 

I. Biederman, “Recognition-by-Components: A Theory of Human Image Understanding”, Psychological Review, Volume 94, 1987, pp 115-147.
http://www.cs.toronto.edu/~sven/2523/Papers/biederman.pdf

 

S. Tulsiani, H. Su, L. Guibas, A. Efros, and J. Malik, “Learning Shape Abstractions by Assembling Volumetric Primitives”, Proceedings, IEEE Conference in Computer Vision and Pattern Recognition, 2017.

http://www.cs.toronto.edu/~sven/2523/Papers/Tulsiani2017.pdf

 

Supplemental:


A. Pentland, “Perceptual Organization and the Representation of Natural Form”, Artificial Intelligence, Volume 28, Number 2, 1986, pp 293-331.
http://www.cs.toronto.edu/~sven/2523/Papers/pentland.pdf

 

A. Gupta, A. Efros, and M. Hebert, Blocks World Revisited: Image Understanding using Qualitative Geometry and Mechanics”, European Conference on Computer Vision (ECCV), September, 2010.

http://www.cs.toronto.edu/~sven/2523/Papers/Gupta2010.pdf

 

10. Deformable Models of Shape in 2-D

 

K. Denisova, J. Feldman, X. Su, and M. Singh, “Investigating shape representation using sensitivity to part- and axis-based transformations”, Vision Research, Volume 126, 2016, pp 347-361.

http://www.cs.toronto.edu/~sven/2523/Papers/Denisova2016.pdf

 

P. Felzenszwalb, “Representation and Detection of Deformable Shapes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 27, Number 2, 2005, pp 208-220.

http://www.cs.toronto.edu/~sven/2523/Papers/Felzenszwalb2005.pdf

 

Supplemental:

 

S. Sclaroff and A. Pentland, “Modal Matching for Correspondence and Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 17, Number 6, 1995, pp 545-561.
http://www.cs.toronto.edu/~sven/2523/Papers/sclaroff.pdf

 

R. Basri, L. Costa, D. Geiger, and D. Jacobs, “Determining the Similarity of Deformable Shapes”, Vision Research, Volume 38, 1998, pp 2365-2385.
http://www.cs.toronto.edu/~sven/2523/Papers/basri.pdf

 

11. Deformable Models of Shape in 3-D

 

P. Sprote and R. Fleming, “Bent out of shape: The visual inference of non-rigid shape transformations applied to objects”, Vision Research, Volume 126, 2016, pp 330-346.

http://www.cs.toronto.edu/~sven/2523/Papers/SproteFleming2016.pdf

 

S. Dickinson and D. Metaxas, “Integrating Qualitative and Quantitative Shape Recovery”, International Journal of Computer Vision, Volume 13, Number 3, 1994, pp 1-20. http://www.cs.toronto.edu/~sven/2523/Papers/DickinsonMetaxas1994.pdf

 

Supplemental:

 

Y. Chen, T.-K. Kim, and R. Cipolla, “Inferring 3D Shapes and Deformations from Single Views”, Proceedings, European Conferene om Computer Vision, 2010.

http://www.cs.toronto.edu/~sven/2523/Papers/Chen2010.pdf

 

A. Kanazawa, S. Kovalsky, R. Basri, and D. Jacobs, “Learning 3D Deformation of Animals from 2D Images”, EUROGRAPHICS 2016, Volume 35, Number 2, 2016.

http://www.cs.toronto.edu/~sven/2523/Papers/Kanazawa2016.pdf

 

Q. Tan, L. Gao, Y.-K. Lai, J. Yang, and S. Xia, “Mesh-based Autoencoders for Localized Deformation Component Analysis”.

https://arxiv.org/abs/1709.04304

 

12. Architectures for Shape Perception

 

M. Riesenhuber and T. Poggio, “Hierarchical models of object recognition in cortex”, Nature Neuroscience, Volume 2, Number 11, 1999, pp 1019-1025.

http://www.cs.toronto.edu/~sven/2523/Papers/RiesenhuberPoggio1999.pdf

 

W. Shen, K. Zhao, Y. Jiang, Y. Wang, X. Bai and A. Yuille, “DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images”, Proceedings, IEEE Conference on Computer Vision and Pattern Recognition, 2016.

http://www.cs.toronto.edu/~sven/2523/Papers/DeepSkeleton.pdf

 

Supplemental:

 

H. Huang, E. Kalogerakis, B. Marlin, “Analysis and synthesis of 3D shape families via deep-learned generative models of surfaces”, Eurographics Symposium on Geometry Processing 2015, Volume 34, Number 5, 2015.

http://www.cs.toronto.edu/~sven/2523/Papers/Huang-AnalysisAndSynthesisOf3DShapeFamilies.pdf

 

J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. B. Tenenbaum, “Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling”, Proceedings, NIPS, 2016.

http://www.cs.toronto.edu/~sven/2523/Papers/Wu2016.pdf

 

C. Nash and C. K. I. Williams, “The shape variational autoencoder: A deep generative model of part-segmented 3D objects”, Eurographics Symposium on Geometry Processing 2017, Volume 36, Number 5, 2017.

http://www.cs.toronto.edu/~sven/2523/Papers/Nash-TheShapeVariationalAutoencoder.pdf