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 Scene Understanding Symposium  posted by  duggu   on 12/12/2007  Add Courseware to favorites Add To Favorites  
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Abstract/Syllabus:

Oliva, Aude, 9.459 Scene Understanding Symposium, Spring 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu (Accessed 08 Jul, 2010). License: Creative Commons BY-NC-SA

A brightly colored image, useful in scene understanding.

Dali et sa mère. (Image courtesy of Michale Fee. Used with permission.)

Course Highlights

This course features lecture notes and associated readings for the presentations given at the 2006 Scene Understanding Symposium.

Course Description

What are the circuits, mechanisms and representations that permit the recognition of a visual scene from just one glance? In this one-day seminar on Scene Understanding, speakers from a variety of disciplines - neurophysiology, cognitive neuroscience, visual cognition, computational neuroscience and computer vision - will address a range of topics related to scene recognition, including natural image categorization, contextual effects on object recognition, and the role of attention in scene understanding and visual art. The goal is to encourage exchanges between researchers of all fields of brain sciences in the burgeoning field of scene understanding

Syllabus

 
 

Description

What are the circuits, mechanisms and representations that permit the recognition of a visual scene from just one glance? In this first symposium on Scene Understanding, speakers from a variety of disciplines - neurophysiology, cognitive neuroscience, visual cognition, computational neuroscience and computer vision - will address a range of topics related to scene recognition, including natural image categorization, contextual effects on object recognition, and the role of attention in scene understanding and visual art. The goal is to encourage exchanges between researchers of all fields of brain sciences in the burgeoning field of scene understanding.

Registration

Admission is free and open to the research community.

Organizers

Prof. Aude Oliva, MIT Brain and Cognitive Sciences

Thomas Serre, MIT McGovern Institute

Antonio Torralba, MIT Computer Science and Artificial Intelligence Laboratory

Sponsored by The Center for Biological and Computational Learning, The Department of Brain and Cognitive Sciences, and The McGovern Institute for Brain Research, MIT.

Calendar

 
 
TIME TOPICS SPEAKERS
8:55 Opening Remarks  
9:00-9:20 From Zero to Gist in 200 msec: The Time Course of Scene Recognition Aude Oliva and Michelle Greene, MIT Brain and Cognitive Sciences
9:20-9:45 Feedforward Theories of Visual Cortex Predict Human Performance in Rapid Image Categorization Thomas Serre and Tomaso Poggio, MIT McGovern Institute
9:45-10:05 Latency, Duration and Codes for Objects in Inferior Temporal Cortex Gabriel Kreiman, Chou Hung, Tomaso Poggio and James DiCarlo, MIT McGovern Institute and Brain and Cognitive Sciences
10:25-10:50 From Feedforward Vision to Natural Vision: The Impact of Free Viewing, Task, and Clutter on Monkey Inferior Temporal Object Representations James DiCarlo, MIT McGovern Institute
10:50-11:10 Invariant Visual Representations of Natural Images by Single Neurons in the Human Brain Leila Reddy (MIT McGovern Institute), Rodrigo Quian Quiroga, Gabriel Kreiman, Christof Koch and Itzhak Fried
11:10-11:40 Perception of Objects in Natural Scenes and the Role of Attention Anne Treisman and Karla Evans, Princeton University
1:00-1:25 Natural Scene Categorization: From Humans to Computers Li Fei-Fei (Beckman Institute, University of Illinois at Urbana-Champaign), Rufin VanRullen, Asha Iyer, Christof Koch and Pietro Perona
1:25-1:50 Contextual Associations in the Brain Moshe Bar, Elissa Aminoff and Nurit Gronau, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
1:50-2:15 Using the Forest to See the Trees: A Computational Model Relating Features, Objects and Scenes Antonio Torralba, MIT Computer Science and Artificial Intelligence Laboratory
2:25-2:45 Detecting and Remembering Pictures With and Without Visual Noise Mary Potter and Ming Meng, MIT Brain and Cognitive Sciences
2:45-3:05 Scene Perception after Those First Few Hundred Milliseconds Jeremy Wolfe, Brigham and Women's Hospital and Harvard Medical School
3:05-3:35 The Artist as Neuroscientist Patrick Cavanagh, Vision Sciences Lab, Department of Psychology, Harvard University
4:00-5:00 Brain and Cognitive Sciences Colloquium - Scene Processing with a Wave of Spikes: Reverse Engineering the Visual System Simon Thorpe, CNRS and SpikeNet Technology, France



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