The perception of a familiar face is no more than the sum of its parts
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- 作者：Jason M. Gold (1)
Jarrett D. Barker (1)
Shawn Barr (1)
Jennifer L. Bittner (1)
Alexander Bratch (1)
W. Drew Bromfield (1)
Roy A. Goode (1)
Mary Jones (1)
Doori Lee (1)
Aparna Srinath (1) - 关键词：Visual perception ; Face perception and recognition ; Bayesian modeling ; Perceptual learning
- 刊名：Psychonomic Bulletin & Review
- 出版年：2014
- 出版时间：December 2014
- 年：2014
- 卷：21
- 期：6
- 页码：1465-1472
- 全文大小：380 KB
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19. Hole, G. J. (1 - 作者单位：Jason M. Gold (1)
Jarrett D. Barker (1)
Shawn Barr (1)
Jennifer L. Bittner (1)
Alexander Bratch (1)
W. Drew Bromfield (1)
Roy A. Goode (1)
Mary Jones (1)
Doori Lee (1)
Aparna Srinath (1)
1. Department of Psychological and Brain Sciences, Indiana University, 1101 East 10th Street, Bloomington, IN, 47405, USA - ISSN：1531-5320
文摘
Why do faces become easier to recognize with repeated exposure? Previous research has suggested that familiarity may induce a qualitative shift in visual processing from an independent analysis of individual facial features to analysis that includes information about the relationships among features (Farah, Wilson, Drain, & Tanaka Psychological Review, 105, 482-98, 1998; Maurer, Grand, & Mondloch Trends in Cognitive Science, 6, 255-60, 2002). We tested this idea by using a “summation-at-threshold-technique (Gold, Mundy, & Tjan Psychological Science, 23, 427-34, 2012; Nandy & Tjan Journal of Vision, 8, 3.1-0, 2008), in which an observer’s ability to recognize each individual facial feature shown independently is used to predict their ability to recognize all of the features shown in combination. We find that, although people are better overall at recognizing familiar as opposed to unfamiliar faces, their ability to integrate information across features is similar for unfamiliar and highly familiar faces and is well predicted by their ability to recognize each of the facial features shown in isolation. These results are consistent with the idea that familiarity has a quantitative effect on the efficiency with which information is extracted from individual features, rather than a qualitative effect on the process by which features are combined.