Conjunction-guided selection in visual search Igor S. Utochkin The National Research University “Higher School of Economics”, Russia.

Slides:



Advertisements
Similar presentations
Selective Visual Attention: Feature Integration Theory PS2009/10 Lecture 9.
Advertisements

Reminder: extra credit experiments
Paula McLaughlin York University Conflict of Interest Disclosure Paula McLaughlin, MA Has no real or apparent conflicts of interest to report. 1.
Palmer (after Broadbent) interval 750 ms test 100 ms cue 250 ms Relevant size 28 (Palmer, after Shaw)
Visual Saliency: the signal from V1 to capture attention Li Zhaoping Head, Laboratory of natural intelligence Department of Psychology University College.
How are Memory and Attention related in Working Memory? Elke Lange, Christian Starzynski, Ralf Engbert University of Potsdam.
Perceptual Processes: Attention & Consciousness Dr. Claudia J. Stanny EXP 4507 Memory & Cognition Spring 2009.
Chapter 6: Visual Attention. Overview of Questions Why do we pay attention to some parts of a scene but not to others? Do we have to pay attention to.
PRIME MINISTRY REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE 1 AGRICULTURAL PRICE STATISTICS Agriculture Statistics Division Agricultural Structure.
Perception and Pattern Recognition  What types of information do we use to perceive the world correctly?  What are the major theories about how we recognize.
CompLACS Composing Learning for Artificial Cognitive Systems Year 2: Specification of scenarios.
NEUR 3680 Midterm II Review Megan Metzler
LOGO Effects of scene inversion on change detection of targets matched for visual salience Professor: Liu Student: Ruby.
Features and Objects in Visual Processing
The visual system Martha Nari Havenith MPI for Brain Research Aug. 5th 2008 FIAS Summer School.
Visual Search: finding a single item in a cluttered visual scene.
Electrophysiology of Visual Attention. Moran and Desimone (1985) “Classical” RF prediction: there should be no difference in responses in these two conditions.
Experiments for Extra Credit Still available Go to to sign upwww.tatalab.ca.
Upcoming Stuff: Finish attention lectures this week No class Tuesday next week – What should you do instead? Start memory Thursday next week – Read Oliver.
Pre-attentive Visual Processing: What does Attention do? What don’t we need it for?
Treisman Visual Search Demo. Visual Search Tasks  Can detect features without applying attention  But detecting stimulus conjunctions requires attention.
Visual Attention More information in visual field than we can process at a given moment Solutions Shifts of Visual Attention related to eye movements Some.
Next Week Memory: Articles by Loftus and Sacks (following week article by Vokey)
Tracking multiple independent targets: Evidence for a parallel tracking mechanism Zenon Pylyshyn and Ron Storm presented by Nick Howe.
Visual search: Who cares?
Types of Perceptual Processes Bottom-up - work up from sensory info. Top-down - apply knowledge and experience.
Attention II Selective Attention & Visual Search.
Features and Object in Visual Processing. The Waterfall Illusion.
Attention II Theories of Attention Visual Search.
PROSEMINAR Environmental Management ENVR E-200. DO YOU HAVE? System for keeping notes on your readings and draft writing Information on your primary target.
Overview Feature inheritance Shine-through Modelling Binding problem Contextual modulation Backward masking Temporal processing Schizophrenia.
Features and Object in Visual Processing. The Waterfall Illusion.
Parallel vs. Serial Information Processing Remember - attention is about information processing.
Read article by Anne Treisman. Reflexive Orienting Attention can be automatically “summoned” to a location at which an important event has occurred: –Loud.
1 Confidence Intervals for Means. 2 When the sample size n< 30 case1-1. the underlying distribution is normal with known variance case1-2. the underlying.
Hypothesis Testing :The Difference between two population mean :
Studying Visual Attention with the Visual Search Paradigm Marc Pomplun Department of Computer Science University of Massachusetts at Boston
DEAD ZONE OF VISUAL ATTENTION REVEALED BY CHANGE BLINDNESS Igor S. Utochkin Higher School of Economics, Moscow, Russia
Manipulating Attention in Computer Games Matthias Bernhard, Le Zhang, Michael Wimmer Institute of Computer Graphics and Algorithms Vienna University of.
Text Lecture 2 Schwartz.  The problem for the designer is to ensure all visual queries can be effectively and rapidly served.  Semantically meaningful.
1 Perception and VR MONT 104S, Fall 2008 Session 13 Visual Attention.
Feature Integration Theory Project guide: Amitabha Mukerjee Course: SE367 Presented by Harmanjit Singh.
Control of Attention in schizophrenia 1.Advance understanding of schizophrenia. Move from description of deficits to explanation of specific mechanisms.
Lecture 4 – Attention 1 Three questions: What is attention? Are there different types of attention? What can we do with attention that we cannot do without.
Modeling Visual Search Time for Soft Keyboards Lecture #14.
Interference from irrelevant color-singletons during serial search depends on visual attention being spatially diffuse Bryan R. Burnham James H. Neely.
Binding problems and feature integration theory. Feature detectors Neurons that fire to specific features of a stimulus Pathway away from retina shows.
Organization of Working Memory— Reconciling Two Different Models Anna Alapatt.
Younger Older AdultsAdults MSDMSD Conjunction minus Feature Right fusiform gyrus (BA 19) Conjunction Feature Right.
“Nothing average ever stood as a monument to progress. When progress is looking for a partner it doesn't turn to those who believe they are only average.
Goals for Today’s Class
VISUAL SEARCH TASK Brendan Ahern, Nathan MacIntyre-Hayes, & Cierra Tompkins.
Notes: 1. Extra Credit – Assignment 5 Due December Last exam December 10 Announcement and instructions on Class communication page 3. Spatial Abilities.
Cognitive approaches: Information processing, with the computer as a model.
Steven Dodd, Christian Kreitz, Lauren Landers, Kelsey Panter.
Assist. Prof. Dr. Ilmiye Seçer Fall
Kimron Shapiro & Frances Garrad-Cole The University of Wales, Bangor
Journal of Vision. 2013;13(3):24. doi: / Figure Legend:
Inference for Proportions
Sampling Fundamentals 2
Chapter 7 Visual Search.
دانشگاه شهیدرجایی تهران
التسعير الفصل الرابع عشر.
تعهدات مشتری در کنوانسیون بیع بین المللی
View from the Top Neuron
Cognitive Processes PSY 334
بسمه تعالی کارگاه ارزشیابی پیشرفت تحصیلی
Cognitive Processes PSY 334
Chapter 7 - Visual Attention
Human vision: function
Presentation transcript:

Conjunction-guided selection in visual search Igor S. Utochkin The National Research University “Higher School of Economics”, Russia

Guided Search (Wolfe, 1994, 1996; 2006): Features can be used to guide visual search What about conjunctions?

Experiments 1 and 2 Color × Orientation targets Set size: 7, 13, or 37 items Features and conjunctions distribution among distractors: Unknown (Exp. 1) vs. Known (Exp. 2) target 2 features, 1/1 2 conjunctions, 1/1 2 features, 1/2 3 conjunctions, 1/1/1 2 features, 1/2 2 conjunctions, 1/2

Experiments 1 and 2 Results

Experiments 3 and 4 Color × Orientation targets Set size: 7, 13, or 37 items Features and conjunctions distribution among distractors: Unknown (Exp. 3) vs. Known (Exp. 4) target NeutralCongruentIncongruent

Experiments 3 and 4 Results

A “tentative binding” hypothesis Approximate, imprecise but not accidental; Requires some global attentional processing prior to focusing on individuals;

I. Distributed attention binds features approximately (Treisman, 2006) II. Limited-capacity parallel binding (Luck & Vogel, 1997) of samples (Simons & Myszek, 2008)

A “tentative binding” hypothesis Approximate, imprecise but not accidental; Requires some global attentional processing prior to focusing on individuals; Primes subsequent allocation of focused attention

Thank you for attention! Acknowledgements: Yulia Stakina Anna Rakova The study was conducted within the Program for basic research of the Higher School of Economics in 2012