Psych 465: Topics in High-Level Vision — Object and Scene Processing

Time and place: T 2:30-4:10; 208 Uris Hall (note change from the published time and place).
Instructors: David Field, Shimon Edelman.

This seminar, intended for graduate students and advanced undergraduates, will survey the state of the art in object recognition and scene interpretation. We shall discuss computational principles behind these cognitive functions and examine up-to-date behavioral data, neurobiological findings (including single-cell and imaging data), and computer models. The material will include, among other topics, the Bayesian framework for perception and generative methods for processing object and scene structure.

NOTE: THIS PAGE IS UNDER CONSTRUCTION!!! Scroll down for the weekly schedule.

theme #	heading	remarks
THEME I	Perception: behavioral findings	remarks
THEME II	The machinery of vision: neurobiology	remarks
THEME III	Modeling: computation	remarks
THEME IV	Image statistics: more computation	remarks
THEME V	Philosophy: the big picture	remarks

Readings by theme

Weekly schedule

Week 2 (1/27)

1. Field DJ. (1994). What is the Goal of Sensory Coding?, Neural Computation 6:559-601. [PDF]
2. Field DJ. (1987). Relations Between the Statistics of Natural Images and the Response Profiles of Cortical Cells. Journal of the Optical Society of America A 4:2379-2394. [PDF]

Week 3 (2/3)

1. Edelman, S. Constraining the neural representation of the visual world, Trends in Cognitive Sciences 6:125-131, 2002.
2. Edelman, S., and N. Intrator. Towards structural systematicity in distributed, statically bound visual representations, Cognitive Science, 27:73-110 (2003).
3. Edelman, S. On what it means to see, and what we can do about it, in Object Categorization: Computer and Human Vision Perspectives, S. Dickinson, A. Leonardis, B. Schiele, and M. J. Tarr, eds. (Cambridge University Press, 2009, in press).

Week 4 (2/10)

1. Edelman, S., and S. Duvdevani-Bar, Similarity-based viewspace interpolation and the categorization of 3D objects, in Proc. Edinburgh Workshop on Similarity and Categorization, 75-81, November 1997.
2. DiCarlo, J. J., and D. D. Cox, Untangling invariant object recognition, Trends in Cognitive Sciences 11:333-341 (2007).

Week 5 (2/17)

1. Qiu FT, von der Heydt R (2005) Figure and ground in the visual cortex: V2 combines stereoscopic cues with Gestalt rules. Neuron 47: 155-166
2. Lennie, P. (1998). Single units and visual cortical organization. Perception, 27, 889-935.

Week 6 (2/24)

1. Bar, M. (2004). Visual Object in Context. Nature Neuroscience Review, 5:617-628.
2. M. Bar, E. Aminoff and D.L. Schacter (2008). Scenes unseen: The parahippocampal cortex intrinsically subserves contextual associations, not scenes or places per se Journal of Neuroscience, 28:8539-8544.

Week 7 (3/3)

1. Brady, T.F., Konkle, T., Alvarez, G.A., & Oliva, A. (2008). Visual long-term memory has a massive storage capacity for object details. Proceedings of the National Academy of Sciences, USA, vol 105 (38), 14325-14329.
2. Oliva, A., and A. Torralba (2007). The role of context in object recognition, TiCS.

Week 8 (3/10)

SPRING BREAK (3/17)

Week 9 (3/24)

1. Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex. James V. Haxby, et al., Science 293:2425-2430 (2001).
2. The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception. Nancy Kanwisher, Josh McDermott, and Marvin M. Chun, The Journal of Neuroscience 17:4302-4311 (1997).
3. Invariant visual representation by single neurons in the human brain. R. Quian Quiroga, L. Reddy, G. Kreiman, C. Koch, and I. Fried, Nature, 435:1102-1107 (2005).

Week 10 (3/31)

1. Goal-Related Activity in V4 during Free Viewing Visual Search: Evidence for a Ventral Stream Visual Salience Map. James A. Mazer and Jack L. Gallant. Neuron 40:1241-1250 (2003).
2. Attention to Stimulus Features Shifts Spectral Tuning of V4 Neurons during Natural Vision. Stephen V. David, Benjamin Y. Hayden, James A. Mazer, and Jack L. Gallant. Neuron 59:509-521 (2008).

Week 11 (4/7)

1. How position dependent is visual object recognition? Dwight J. Kravitz, Latrice D. Vinson and Chris I. Baker. Trends in Cognitive Sciences 12:114-122 (2008).
2. The interaction of shape- and location-based priming in object categorisation: Evidence for a hybrid "what + where" representation stage. Fiona N. Newell, Dianne M. Sheppard, Shimon Edelman, and Kimron L. Shapiro. Vision Research 45:2065-2080 (2005).
3. Lomber, S. G., & Malhotra, S. Double dissociation of 'what' and 'where' processing in auditory cortex. Nature Neuroscience, 11:609-616 (2008).

Week 12 (4/14)

1. Transformation of shape information in the ventral pathway. Charles E Connor, Scott L Brincat and Anitha Pasupathy. Current Opinion in Neurobiology 17:140-147 (2007).
2. A neural code for three-dimensional object shape in macaque inferotemporal cortex. Yukako Yamane, Eric T Carlson, Katherine C Bowman, Zhihong Wang & Charles E Connor. Nature Neuroscience 11:1352-1360 (2008).

Week 13 (4/21)

1. Hierarchical models of object recognition in cortex. Maximilian Riesenhuber and Tomaso Poggio. Nature Neuroscience 2:1019-1026 (1999).
2. Complex objects are represented in macaque inferotemporal cortex by the combination of feature columns. Kazushige Tsunoda, Yukako Yamane, Makoto Nishizaki, and Manabu Tanifuji. Nature Neuroscience 4:832-839 (2001).

Week 14 (4/28)

1. J. Hollingworth. Visual Memory for Natural scenes. In Visual Memory Ed. Luck and Hollingworth.