Ensemble Coding
Ensemble coding, also known as ensemble perception or summary representation, is the ability to see the average or variance of a group of objects. This is often referred to as taking summary statistical information. Put simply, it is a theory that suggests that people process the general gist of their complex visual surroundings by grouping them together based on their similarities. People are able to extract the gist of ensembles across various dimensions because the visual world is filled with redundant information. [1] Extant literature has shown that the visual system is particularly sensitive to similarities and organization that occurs naturally in our visual world.[2]
Ensemble Coding Defined
David Whitney and Allison Yamanashi Lieb developed an operational and flexible definition stating that, “...ensemble coding should include the following five concepts:
- Ensemble perception is the ability to discriminate or reproduce a statistical moment.
- Ensemble perception requires the integration of multiple items.
- Ensemble information at each level of representation can be precise relative to the processing of single objects at that level.
- Single-item recognition is not a prerequisite for ensemble coding.
- Ensemble representations can be extracted with a temporal resolution at or beyond the temporal resolution of individual object recognition.” [1]
Opposing Theories
Counter to the idea that people get a general gist of our visual surroundings by way of summary statistics. Some research in vision science has noted that although humans take in large amounts of visual information, adults are only able to process, attend to, and hold in memory up to about four items from the visual environment. [4] [5]
Historical Context
Gestalt Theorists
Ensemble coding is a theory that was established by vision scientists, but is now used by various disciplines. Vision Scientists have expressed interest in how people perceive groups of objects for quite some time. This interest has developed from low-level perceptual processes to high-level perceptual processes spanning multiple disciplines.
The Current Era
Ariely 2001 [6]
Levels of Ensemble Coding
All levels suggest the ability to obtain a statistical average and variance of groups or multiple groups.
Low-Level
Mid-Level
High-Level
Social Ensemble Coding
History
Social Vision of groups and social categorization
This is a user sandbox of Ensemble coding. You can use it for testing or practicing edits. This is not the place where you work on your assigned article for a dashboard.wikiedu.org course. Visit your Dashboard course page and follow the links for your assigned article in the My Articles section. |
This template should only be used in the user namespace.This template should only be used in the user namespace.
- ^ a b Whitney, David; Yamanashi Leib, Allison (2018). "Ensemble Perception". Annual Review of Psychology. 69 (1): 105–129. doi:10.1146/annurev-psych-010416-044232. PMID 28892638.
- ^ Whitney D, Haberman J, Sweeny T. 2014. From textures to crowds: multiple levels of summary statistical perception. In The New Visual Neuroscience, ed. JS Werner, LM Chalupa, pp. 695–710. Cambridge, MA: MIT Press
- ^ Haberman, Jason; Whitney, David (2012-05-24), Wolfe, Jeremy; Robertson, Lynn (eds.), "Ensemble Perception", From Perception to Consciousness, Oxford University Press, pp. 339–349, doi:10.1093/acprof:osobl/9780199734337.003.0030, ISBN 978-0-19-973433-7, retrieved 2019-11-24
- ^ Alvarez, G.A.; Cavanagh, P. (2004-02). "The Capacity of Visual Short-Term Memory is Set Both by Visual Information Load and by Number of Objects". Psychological Science. 15 (2): 106–111. doi:10.1111/j.0963-7214.2004.01502006.x. ISSN 0956-7976.
{{cite journal}}: Check date values in:|date=(help) - ^ Luck, Steven J.; Vogel, Edward K. (1997-11). "The capacity of visual working memory for features and conjunctions". Nature. 390 (6657): 279–281. doi:10.1038/36846. ISSN 1476-4687.
{{cite journal}}: Check date values in:|date=(help) - ^ Ariely, Dan (2001). "Seeing Sets: Representation by Statistical Properties". Psychological Science. 12 (2): 157–162. ISSN 0956-7976.