Learning influences the encoding of static and dynamic faces and their recognition across different spatial frequencies

Visual Cognition

Volumn 17, Issue 5, 2009, Pages 716-735

  Pilz, Karin S ^a   Bülthoff, Heinrich H ^b   Vuong, Quoc C ^c  

^a MCMASTER UNIVERSITY   (Canada)

^b MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

^c NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

Face recognition; Facial motion; Spatial frequency

Indexed keywords

ADULT; ARTICLE; BEHAVIOR; CONTROLLED STUDY; FACE; FEMALE; HUMAN; HUMAN EXPERIMENT; LEARNING; LEARNING STYLE; MALE; PRIORITY JOURNAL; RECOGNITION; SPATIAL FREQUENCY DISCRIMINATION; TASK PERFORMANCE; VISUAL STIMULATION;

EID: 68449085642     PISSN: 13506285     EISSN: 14640716     Source Type: Journal    
DOI: 10.1080/13506280802340588     Document Type: Article

References (43)

1. Bassili, J. N. (1978). Facial motion in the perception of faces and of emotional expression. Journal Experimental Psychology: Human Perception and Performance, 4, 373-9.
2. Bower, G. H., & Karlin, M. B. (1974). Depth of processing pictures of faces and recognition memory. Journal of Experimental Psychology, 103, 751-757.
3. Brainard, D. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433-436.
4. Breitmeyer, B. G. (1975). Simple reaction time as a measure of the temporal response properties of transient and sustained channels. Vision Research, 15, 1411-1412.
5. Costen, N. P., Parker, D. M., & Craw, I. (1994). Spatial content and spatial quantization effects in face recognition. Perception, 23, 129-146.
6. Costen, N. P., Parker, D. M., & Craw, I. (1996). Effects of high-pass and low-pass spatial filtering on face identification. Perception and Psychophysics, 58, 602-612.
7. Fiorentini, A., Maffei, L., & Sandini, G. (1983). The role of high spatial frequencies in face perception. Perception, 12, 195-201.
8. Ginsburg, A. P. (1978). Visual information processing based on spatial filters constrained by biological data. Unpublished doctoral dissertation, Cambridge University, Cambridge, UK.
9. Gish, K., Shulman, G. L., Sheehy, J. B., & Leibowitz, H. W. (1986). Reaction times to different spatial frequencies as a function of detectability. Vision Research, 26, 745-747.
10. Goffaux, V., Hault, B., Michel, C., Vuong, Q. C., & Rossion, B. (2005). The respective role of low and high spatial frequencies in supporting configural and featural processing of faces. Perception, 34, 77-86.
11. Goffaux, V., & Rossion, B. (2006). Faces are "spatial": Holistic face perception is supported by low spatial frequencies. Journal of Experimental Psychology: Human Perception and Performance, 32, 1023-1039.
12. Hayes, A., Morrone, M. C., & Burr, D. C. (1986). Recognition of positive and negative band-pass filtered images. Perception, 15, 595-602.
13. Hill, H., & Johnston, A. (2001). Categorizing sex and identity from the biological motion of faces. Current Biology, 11, 880-887.
14. Kamachi, M., Bruce, V., Mukaida, S., Gyoba, J., Yoshikawa, S., & Akamatsu, S. (2001). Dynamic properties influence the perception of facial expressions. Perception, 30, 875-87.
15. Knight, B., & Johnson, A. (1997). The role of movement in face recognition. Visual Cognition, 4, 265-273.
16. Lander, K., & Bruce, V. (2000). Recognizing famous faces: Exploring the benefits of facial motion. Ecological Psychology, 12, 259-272.
17. Lander, K., & Bruce, V. (2003). The role of motion in learning new faces. Visual Cognition, 10, 897-921.
18. Lander, K., Christie, F., & Bruce, V. (1999). The role of movement in the recognition of famous faces. Memory and Cognition, 27, 974-985.
19. Lander, K., & Chuang, L. (2005). Why are moving faces easier to recognize? Visual Cognition, 12(3), 429-442.
20. Maurer, D., Le Grand, R., & Mondloch, C. J. (2002). The many faces of configural processing. Trends in Cognitive Science, 6(6), 255-260.
21. Megreya, A. M., & Burton, A. M. (2006). Unfamiliar faces are not faces: Evidence from a matching task. Memory and Cognition, 34(4), 865-876.
22. Morrison, D. J., & Schyns, P. G. (2001). Usage of spatial scales for the categorization of faces, objects and scenes. Psychonomic Bulletin and Review, 8, 454-469.
23. Näsänen, R. (1999). Spatial-frequency bandwidth used in the recognition of facial images. Vision Research, 39, 3824-3833.
24. Oliva, A., & Schyns, P. G. (1997). Coarse blobs or fine edges? Evidence that information diagnosticity changes the perception of complex visual stimuli. Cognitive Psychology, 34, 72-107.
25. Palmer, S. (1993). Modern theories of gestalt perception. In G. W. Humphreys (Ed.), Understanding vision (pp. 39-70). Oxford, UK: Blackwell.
26. Parker, D. M., Lishman, J. R., & Hughes, J. (1992). Temporal integration of spatially filtered visual images. Perception, 21, 147-160.
27. Parker, D. M., Lishman, J. R., & Hughes, J. (1997). Evidence for the view that temporospatial integration in vision is temporally anisotropic. Perception, 26, 1169-1180.
28. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437-442.
29. Peyrin, C., Chauvin, A., Chokron, S., & Marendaz, C. (2003). Hemispheric specialization for spatial frequency processing in the analysis of natural scenes. Brain and Cognition, 53, 278-282.
30. Pike, G. E., Kemp, R. I., Towell, N. A., & Phillips, K. C. (1997). Recognizing moving faces: The relative contribution of motion and perspective view information. Visual Cognition, 4, 409-437.
31. Pilz, K. S., Thornton, I. M., & Bülthoff, H. H. (2006). A search advantage for faces learned in motion. Experimental Brain Research 171(4), 436-447.
32. Schwaninger, A., Lobmeier, J. S., & Collishaw, S. M. (2002). The role of featural and configural information in familiar and unfamiliar face recognition. Lecture Notes in Computer Science, 2525, 643-650.
33. Schyns, P. G., & Oliva, A. (1994). From blobs to boundary edges: Evidence for time and spatial-scale-dependent scene recognition. Psychological Science, 5, 195-200.
34. Schyns, P. G., & Oliva, A. (1999). Dr. Angry and Mr. Smile: When categorization flexibly modifies the perception of faces in rapid visual presentations. Cognition, 69, 243-265.
35. Sergent, J. (1986). Microgenesis of face perception. In H. D. Ellis,M. A. Jeeves, F. Newcombe, & A.M. Young (Eds.), Aspects of face processing (pp. 17-33). Dordrecht, The Netherlands: Martinus Nijhoff.
36. Snowden, P. T., & Schyns, P. G. (2006). Channel surfing in the visual brain. Trends in Cognitive Science, 10(12), 538-545.
37. Tanaka, J. W., & Farah, M. J. (1993). Parts and wholes in face recognition. Quarterly Journal of Experimental Psychology, 46 4), 225-245.
38. Thornton, I. M., & Kourtzi, Z. (2002). A matching advantage for dynamic faces. Perception, 31, 113-132.
39. Tieger, T., & Ganz, L. (1979). Recognition of faces in the presence of two-dimensional sinusoidal masks. Perception and Psychophysics, 26, 163-167.
40. Valentine, T. (1988). Upside-down faces: A review of the effect of inversion upon face recognition. British Journal of Psychology, 79, 471-491.
41. Wallis, G., & Bülthoff, H. H. (2001). Effects of temporal association on recognition memory. Proceedings of the National Academy of Sciences, 98, 4800-4804.
42. Wolfe, J. M. (1998). Visual search. In H. Pashler (Ed.), Attention (pp. 13-73). Hove, UK: Psychology Press.
43. Yin, R. K. (1969). Looking at upside-down faces. Journal of Experimental Psychology, 81, 141-145.