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Journal articles on the topic 'Face processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

Jin, Haiyang, Luyan Ji, Olivia S. Cheung, and William G. Hayward. "Two faces of holistic face processing." Journal of Vision 21, no. 9 (September 27, 2021): 2553. http://dx.doi.org/10.1167/jov.21.9.2553.

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2

Mondloch, Catherine J., Richard Le Grand, and Daphne Maurer. "Configural Face Processing Develops more Slowly than Featural Face Processing." Perception 31, no. 5 (May 2002): 553–66. http://dx.doi.org/10.1068/p3339.

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Expertise in face processing takes many years to develop. To determine the contribution of different face-processing skills to this slow development, we altered a single face so as to create sets of faces designed to measure featural, configural, and contour processing. Within each set, faces differed only in the shape of the eyes and mouth (featural set), only in the spacing of the eyes and mouth (spacing set), or only in the shape of the external contour (contour set). We presented adults, and children aged 6, 8, and 10 years, with pairs of upright and inverted faces and instructed them to indicate whether the two faces were the same or different. Adults showed a larger inversion effect for the spacing set than for the featural and external contour sets, confirming that the spacing set taps configural processing. On the spacing set, all groups of children made more errors than adults. In contrast, on the external contour and featural sets, children at all ages were almost as accurate as adults, with no significant difference beginning at age 6 on the external contour set and beginning at age 10 on the featural set. Overall, the results indicate that adult expertise in configural processing is especially slow to develop.

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3

Murphy, Jennifer, Katie L. H. Gray, and Richard Cook. "Inverted faces benefit from whole-face processing." Cognition 194 (January 2020): 104105. http://dx.doi.org/10.1016/j.cognition.2019.104105.

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4

Takahashi, Hiroki. "Face Information Processing." Journal of The Institute of Image Information and Television Engineers 61, no. 4 (2006): 447–52. http://dx.doi.org/10.3169/itej.61.447.

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5

Johnson, Mark H. "Subcortical face processing." Nature Reviews Neuroscience 6, no. 10 (October 2005): 766–74. http://dx.doi.org/10.1038/nrn1766.

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6

Lederman, Susan J., Andrea Kilgour, Ryo Kitada, Roberta L. Klatzky, and Cheryl Hamilton. "Haptic face processing." Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale 61, no. 3 (2007): 230–41. http://dx.doi.org/10.1037/cjep2007024.

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7

Sugita, Yoichi. "Innate face processing." Current Opinion in Neurobiology 19, no. 1 (February 2009): 39–44. http://dx.doi.org/10.1016/j.conb.2009.03.001.

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8

BOOKHEIMER, SUSAN Y., A. TING WANG, ASHLEY SCOTT, MARIAN SIGMAN, and MIRELLA DAPRETTO. "Frontal contributions to face processing differences in autism: Evidence from fMRI of inverted face processing." Journal of the International Neuropsychological Society 14, no. 6 (October 27, 2008): 922–32. http://dx.doi.org/10.1017/s135561770808140x.

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AbstractFunctional neuroimaging studies of face processing deficits in autism have typically focused on visual processing regions, such as the fusiform face area (FFA), which have shown reduced activity in autism spectrum disorders (ASD), though inconsistently. We recently reported reduced activity in the inferior frontal region in ASD, implicating impaired mirror-neuron systems during face processing. In the present study, we used fMRI during a face processing task in which subjects had to match faces presented in the upright versus inverted position. Typically developing (TD) children showed a classic behavioral inversion effect, increased reaction time for inverted faces, while this effect was significantly reduced in ASD subjects. The fMRI data showed similar responses in the fusiform face area for ASD and TD children, with both groups demonstrating increased activation for inverted faces. However, the groups did differ in several brain regions implicated in social cognition, particularly prefrontal cortex and amygdala. These data suggest that the behavioral differences in processing upright versus inverted faces for TD children are related not to visual information processing but to the social significance of the stimuli. Our results are consistent with other recent studies implicating frontal and limbic dysfunction during face processing in autism. (JINS, 2008, 14, 922–932.)

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Besson, G., G. Barragan-Jason, S. J. Thorpe, M. Fabre-Thorpe, S. Puma, M. Ceccaldi, and E. J. Barbeau. "From face processing to face recognition: Comparing three different processing levels." Cognition 158 (January 2017): 33–43. http://dx.doi.org/10.1016/j.cognition.2016.10.004.

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10

Bublatzky, Florian, Andre Pittig, Harald T. Schupp, and Georg W. Alpers. "Face-to-face: Perceived personal relevance amplifies face processing." Social Cognitive and Affective Neuroscience 12, no. 5 (February 1, 2017): 811–22. http://dx.doi.org/10.1093/scan/nsx001.

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11

Young, Andrew W., Hadyn D. Ellis, T. Krystyna Szulecka, and Karel W. De Pauw. "Face Processing Impairments and Delusional Misidentification." Behavioural Neurology 3, no. 3 (1990): 153–68. http://dx.doi.org/10.1155/1990/598170.

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We report detailed investigations of the face processing abilities of four patients who had shown symptoms involving delusional misidentification. One (GC) was diagnosed as a Frégoli case, and the other three (SL, GS, and JS) by symptoms of intermetamorphosis. The face processing tasks examined their ability to recognize emotional facial expressions, identify familiar faces, match photographs of unfamiliar faces, and remember photographs of faces of unfamiliar people. The Frégoli patient (GC) was impaired at identifying familiar faces, and severely impaired at matching photographs of unfamiliar people wearing different disguises to undisguised views. Two of the intermetamorphosis patients (SL and GS) also showed impaired face processing abilities, but the third US) performed all tests at a normal level. These findings constrain conceptions of the relation between delusional misidentification, face processing impairment, and brain injury.

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12

Heisz, Jennifer J., and Judith M. Shedden. "Semantic Learning Modifies Perceptual Face Processing." Journal of Cognitive Neuroscience 21, no. 6 (June 2009): 1127–34. http://dx.doi.org/10.1162/jocn.2009.21104.

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Face processing changes when a face is learned with personally relevant information. In a five-day learning paradigm, faces were presented with rich semantic stories that conveyed personal information about the faces. Event-related potentials were recorded before and after learning during a passive viewing task. When faces were novel, we observed the expected N170 repetition effect—a reduction in amplitude following face repetition. However, when faces were learned with personal information, the N170 repetition effect was eliminated, suggesting that semantic information modulates the N170 repetition effect. To control for the possibility that a simple perceptual effect contributed to the change in the N170 repetition effect, another experiment was conducted using stories that were not related to the person (i.e., stories about rocks and volcanoes). Although viewers were exposed to the faces an equal amount of time, the typical N170 repetition effect was observed, indicating that personal semantic information associated with a face, and not simply perceptual exposure, produced the observed reduction in the N170 repetition effect. These results are the first to reveal a critical perceptual change in face processing as a result of learning person-related information. The results have important implications for researchers studying face processing, as well as learning and memory in general, as they demonstrate that perceptual information alone is not enough to establish familiarity akin to real-world person learning.

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13

Farzin, F., S. Rivera, and D. Whitney. "Holistic face processing in infants using mooney faces." Journal of Vision 8, no. 6 (March 19, 2010): 195. http://dx.doi.org/10.1167/8.6.195.

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14

Elms, N. M., C. J. Mondloch, D. Maurer, W. G. Hayward, G. Rhodes, J. Tanaka, and G. Zhou. "Other-race faces: Limitations of expert face processing." Journal of Vision 8, no. 6 (March 20, 2010): 260. http://dx.doi.org/10.1167/8.6.260.

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15

Jemel, Boutheina, Laurent Mottron, and Michelle Dawson. "Impaired Face Processing in Autism: Fact or Artifact?" Journal of Autism and Developmental Disorders 36, no. 1 (January 2006): 91–106. http://dx.doi.org/10.1007/s10803-005-0050-5.

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16

Kovács, Petra, Balázs Knakker, Petra Hermann, Gyula Kovács, and Zoltán Vidnyánszky. "Face inversion reveals holistic processing of peripheral faces." Cortex 97 (December 2017): 81–95. http://dx.doi.org/10.1016/j.cortex.2017.09.020.

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17

Guan, Lili, Mingming Qi, Haijiang Li, Glenn Hitchman, Juan Yang, and Yijun Liu. "Priming with threatening faces modulates the self-face advantage by enhancing the other-face processing rather than suppressing the self-face processing." Brain Research 1608 (May 2015): 97–107. http://dx.doi.org/10.1016/j.brainres.2015.03.002.

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18

Smith, W. A. P. "Editorial: 3D Face Processing." IET Computer Vision 3, no. 2 (2009): 47. http://dx.doi.org/10.1049/iet-cvi.2009.9036.

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19

Katsnelson, A. "Inner Workings: Face processing." Proceedings of the National Academy of Sciences 111, no. 28 (July 15, 2014): 10023. http://dx.doi.org/10.1073/pnas.1409873111.

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20

Osborne, Cara D., and Sarah V. Stevenage. "Familiarity and face processing." Quarterly Journal of Experimental Psychology 66, no. 1 (January 2013): 108–20. http://dx.doi.org/10.1080/17470218.2012.699077.

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21

Tovée, Martin J. "Is Face Processing Special?" Neuron 21, no. 6 (December 1998): 1239–42. http://dx.doi.org/10.1016/s0896-6273(00)80644-3.

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22

Pascalis, Olivier, Xavier de Martin de Viviés, Gizelle Anzures, Paul C. Quinn, Alan M. Slater, James W. Tanaka, and Kang Lee. "Development of face processing." Wiley Interdisciplinary Reviews: Cognitive Science 2, no. 6 (April 15, 2011): 666–75. http://dx.doi.org/10.1002/wcs.146.

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23

P.Dahake, R., and M. U. Kharat. "Face Detection and Processing: a Survey." International Journal of Engineering & Technology 7, no. 4.19 (November 27, 2018): 1066. http://dx.doi.org/10.14419/ijet.v7i4.19.28287.

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In the recent era facial image processing is gaining more importance and the face detection from image or from video have number of applications which are video surveillance, entertainment, security, multimedia, communication, Ubiquitous computing etc. Various research work are carried out for face detection and processing which includes detection, tracking of the face, estimation of pose, clustering the detected faces etc. Although significant advances have been made, the performance of face detection systems provide satisfactory under controlled environment & may get degraded with some challenging scenario such as in real time video face detection and processing. There are many real-time applications where human face serves as identity and these application are time bound so time for detection of face from image or video and the further processing is very essential, thus here our goal is to discuss the face detection system overview and to review various human skin colors based approaches and Haar feature based approach for better detection performance. Detected faces tagging and clustering is essential in some cases, so for such further processing time factor plays important role. Some of the recent approaches to improve detection speed such as using Graphical Processing Unit are discussed and providing future directions in this area.

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24

Bombari, Dario, Nora Preuss, and Fred W. Mast. "Lateralized Processing of Faces." Swiss Journal of Psychology 73, no. 4 (January 2014): 215–24. http://dx.doi.org/10.1024/1421-0185/a000140.

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We investigated the lateralized processing of featural and configural information in face recognition in two divided visual field studies. In Experiment 1, participants matched the identity of a cue face containing either featural (scrambled faces) or configural (blurred faces) information with an intact test face presented subsequently either in the right visual field (RVF) or in the left visual field (LVF). Unilateral presentation was controlled by monitoring eye movements. The results show an advantage of the left hemisphere (LH) over the right hemisphere (RH) for featural processing and a specialization of the RH for configural compared to featural processing. In Experiment 2, we focused on configural processing and its relationship to familiarity. Either learned or novel test faces were presented in the LVF or the RVF. Participants recognized learned faces better when presented in the LVF than in the RVF, suggesting that the RH has an advantage in the recognition of learned faces. Because the recognition of familiar faces relies strongly on configural information ( Buttle & Raymond, 2003 ), we argue that the advantage of the RH over the LH in configural processing is a function of familiarity.

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25

Huntsberger, Terry, John Rose, and Shashidhar Ramaka. "Fuzzy-Face." Journal of Biological Systems 06, no. 03 (September 1998): 281–98. http://dx.doi.org/10.1142/s0218339098000194.

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The human face is one of the most important patterns our visual system receives. It establishes a person's identity and also plays a significant role in everyday communication. Humans can recognize familiar faces under varying lighting conditions, different scales, and even after the face has changed due to aging, hair style, glasses, or facial hair. Our ease at recognizing faces is a strong motivation for the investigation of computational models of face processing. This paper presents a newly developed face processing system called Fuzzy-Face that combines wavelet pre-processing of input with a fuzzy self-organizing feature map algorithm. The wavelet-derived face space is partitioned into fuzzy sets which are characterized by face exemplars and membership values to those exemplars. This system learns faces using relatively few training epochs, has total recall for faces it has been shown, generalizes to face images that are acquired under different lighting conditions, and has rudimentary gender discrimination capabilities. We also include the results of some experimental studies.

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26

Zhang, Hong, Yaoru Sun, and Lun Zhao. "Face Context Influences Local Part Processing: An ERP Study." Perception 46, no. 9 (February 2, 2017): 1090–104. http://dx.doi.org/10.1177/0301006617691293.

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Perception of face parts on the basis of features is thought to be different from perception of whole faces, which is more based on configural information. Face context is also suggested to play an important role in face processing. To investigate how face context influences the early-stage perception of facial local parts, we used an oddball paradigm that tested perceptual stages of face processing rather than recognition. We recorded the event-related potentials (ERPs) elicited by whole faces and face parts presented in four conditions (upright-normal, upright-thatcherised, inverted-normal and inverted-thatcherised), as well as the ERPs elicited by non-face objects (whole houses and house parts) with corresponding conditions. The results showed that face context significantly affected the N170 with increased amplitudes and earlier peak latency for upright normal faces. Removing face context delayed the P1 latency but did not affect the P1 amplitude prominently for both upright and inverted normal faces. Across all conditions, neither the N170 nor the P1 was modulated by house context. The significant changes on the N170 and P1 components revealed that face context influences local part processing at the early stage of face processing and this context effect might be specific for face perception. We further suggested that perceptions of whole faces and face parts are functionally distinguished.

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27

Muhammad Nadeem Ali. "Face and Face Parts Detection in Image Processing." Lahore Garrison University Research Journal of Computer Science and Information Technology 1, no. 1 (March 31, 2017): 62–68. http://dx.doi.org/10.54692/lgurjcsit.2017.01017.

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This paper based on a procedure for automatically detecting one ormore human faces, eyes pair, nose, mouth in colour images. This is dependingon two-method which first detects regions of face, eyes pair, nose, mouth containhuman skin in the colour image and then extracts information from these regionsand then detect the regions which include face, eyes pair, mouth, nose in thecolour image. The face, eyes pair, mouth, nose identified is completed on acolour image having only the identified image parts. An arrangement of threshholding and calculated values and some functions are used to remove itemstructures that would show the existence of an identified area.

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Michel, C., O. Corneille, and B. Rossion. "Categorization of face race modulates holistic face processing." Journal of Vision 6, no. 6 (March 19, 2010): 435. http://dx.doi.org/10.1167/6.6.435.

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29

Bindemann, Markus, Rob Jenkins, and A. Mike Burton. "A Bottleneck in Face Identification." Experimental Psychology 54, no. 3 (January 2007): 192–201. http://dx.doi.org/10.1027/1618-3169.54.3.192.

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Abstract. There is evidence that face processing is capacity-limited in distractor interference tasks and in tasks requiring overt recognition memory. We examined whether capacity limits for faces can be observed with a more sensitive measure of visual processing, by measuring repetition priming of flanker faces that were presented alongside a face or a nonface target. In Experiment 1, we found identity priming for face flankers, by measuring repetition priming across a change in image, during task-relevant nonface processing, but not during the processing of a concurrently-presented face target. Experiment 2 showed perceptual priming of the flanker faces, across identical images at prime and test, when they were presented alongside a face target. In a third Experiment, all of these effects were replicated by measuring identity priming and perceptual priming within the same task. Overall, these results imply that face processing is capacity limited, such that only a single face can be identified at one time. Merely attending to a target face appears sufficient to trigger these capacity limits, thereby extinguishing identification of a second face in the display, although our results demonstrate that the additional face remains at least subject to superficial image processing.

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30

Fisher, Clark, and Winrich A. Freiwald. "Whole-agent selectivity within the macaque face-processing system." Proceedings of the National Academy of Sciences 112, no. 47 (October 13, 2015): 14717–22. http://dx.doi.org/10.1073/pnas.1512378112.

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The primate brain contains a set of face-selective areas, which are thought to extract the rich social information that faces provide, such as emotional state and personal identity. The nature of this information raises a fundamental question about these face-selective areas: Do they respond to a face purely because of its visual attributes, or because the face embodies a larger social agent? Here, we used functional magnetic resonance imaging to determine whether the macaque face patch system exhibits a whole-agent response above and beyond its responses to individually presented faces and bodies. We found a systematic development of whole-agent preference through the face patches, from subadditive integration of face and body responses in posterior face patches to superadditive integration in anterior face patches. Superadditivity was not observed for faces atop nonbody objects, implying categorical specificity of face–body interaction. Furthermore, superadditivity was robust to visual degradation of facial detail, suggesting whole-agent selectivity does not require prior face recognition. In contrast, even the body patches immediately adjacent to anterior face areas did not exhibit superadditivity. This asymmetry between face- and body-processing systems may explain why observers attribute bodies’ social signals to faces, and not vice versa. The development of whole-agent selectivity from posterior to anterior face patches, in concert with the recently described development of natural motion selectivity from ventral to dorsal face patches, identifies a single face patch, AF (anterior fundus), as a likely link between the analysis of facial shape and semantic inferences about other agents.

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Bentin, Shlomo, Noam Sagiv, Axel Mecklinger, Angela Friederici, and Yves D. von Cramon. "Priming Visual Face-Processing Mechanisms: Electrophysiological Evidence." Psychological Science 13, no. 2 (March 2002): 190–93. http://dx.doi.org/10.1111/1467-9280.00435.

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Accumulated evidence from electrophysiology and neuroimaging suggests that face perception involves extrastriate visual mechanisms specialized in processing physiognomic features and building a perceptual representation that is categorically distinct and can be identified by face-recognition units. In the present experiment, we recorded event-related brain potentials in order to explore possible contextual influences on the activity of this perceptual mechanism. Subjects were first exposed to pairs of small shapes, which did not elicit any face-specific brain activity. The same stimuli, however, elicited face-specific brain activity after subjects saw them embedded in schematic faces, which probably primed the subjects to interpret the shapes as schematic eyes. No face-specific activity was observed when objects rather than faces were used to form the context. We conclude that the activity of face-specific extrastriate perceptual mechanisms can be modulated by contextual constraints that determine the significance of the visual input.

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Taubert, Jessica, David Aagten-Murphy, and Lisa A. Parr. "A Comparative Study of Face Processing Using Scrambled Faces." Perception 41, no. 4 (January 2012): 460–73. http://dx.doi.org/10.1068/p7151.

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33

Pannese, Alessia, and Joy Hirsch. "Self-face enhances processing of immediately preceding invisible faces." Neuropsychologia 49, no. 3 (February 2011): 564–73. http://dx.doi.org/10.1016/j.neuropsychologia.2010.12.019.

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34

Itier, Roxane J., Claude Alain, Katherine Sedore, and Anthony R. McIntosh. "Early Face Processing Specificity: It's in the Eyes!" Journal of Cognitive Neuroscience 19, no. 11 (November 2007): 1815–26. http://dx.doi.org/10.1162/jocn.2007.19.11.1815.

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Unlike most other objects that are processed analytically, faces are processed configurally. This configural processing is reflected early in visual processing following face inversion and contrast reversal, as an increase in the N170 amplitude, a scalp-recorded event-related potential. Here, we show that these face-specific effects are mediated by the eye region. That is, they occurred only when the eyes were present, but not when eyes were removed from the face. The N170 recorded to inverted and negative faces likely reflects the processing of the eyes. We propose a neural model of face processing in which face- and eye-selective neurons situated in the superior temporal sulcus region of the human brain respond differently to the face configuration and to the eyes depending on the face context. This dynamic response modulation accounts for the N170 variations reported in the literature. The eyes may be central to what makes faces so special.

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Żochowska, Anna, Maria M. Nowicka, Michał J. Wójcik, and Anna Nowicka. "Self-face and emotional faces—are they alike?" Social Cognitive and Affective Neuroscience 16, no. 6 (February 8, 2021): 593–607. http://dx.doi.org/10.1093/scan/nsab020.

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Abstract The image of one’s own face is a particularly distinctive feature of the self. The self-face differs from other faces not only in respect of its familiarity but also in respect of its subjective emotional significance and saliency. The current study aimed at elucidating similarities/dissimilarities between processing of one’s own face and emotional faces: happy faces (based on the self-positive bias) and fearful faces (because of their high perceptual saliency, a feature shared with self-face). Electroencephalogram data were collected in the group of 30 participants who performed a simple detection task. Event-related potential analyses indicated significantly increased P3 and late positive potential amplitudes to the self-face in comparison to all other faces: fearful, happy and neutral. Permutation tests confirmed the differences between the self-face and all three types of other faces for numerous electrode sites and in broad time windows. Representational similarity analysis, in turn, revealed distinct processing of the self-face and did not provide any evidence in favour of similarities between the self-face and emotional (either negative or positive) faces. These findings strongly suggest that the self-face processing do not resemble those of emotional faces, thus implying that prioritized self-referential processing is driven by the subjective relevance of one’s own face.

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36

Boutet, Isabelle, and Bozana Meinhardt-Injac. "Age Differences in Face Processing: The Role of Perceptual Degradation and Holistic Processing." Journals of Gerontology: Series B 74, no. 6 (January 24, 2018): 933–42. http://dx.doi.org/10.1093/geronb/gbx172.

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Abstract Objectives We simultaneously investigated the role of three hypotheses regarding age-related differences in face processing: perceptual degradation, impaired holistic processing, and an interaction between the two. Methods Young adults (YA) aged 20–33-year olds, middle-age adults (MA) aged 50–64-year olds, and older adults (OA) aged 65–82-year olds were tested on the context congruency paradigm, which allows measurement of face-specific holistic processing across the life span (Meinhardt-Injac, Persike & Meinhardt, 2014. Acta Psychologica, 151, 155–163). Perceptual degradation was examined by measuring performance with faces that were not filtered (FSF), with faces filtered to preserve low spatial frequencies (LSF), and with faces filtered to preserve high spatial frequencies (HSF). Results We found that reducing perceptual signal strength had a greater impact on MA and OA for HSF faces, but not LSF faces. Context congruency effects were significant and of comparable magnitude across ages for FSF, LSF, and HSF faces. By using watches as control objects, we show that these holistic effects reflect face-specific mechanisms in all age groups. Discussion Our results support the perceptual degradation hypothesis for faces containing only HSF and suggest that holistic processing is preserved in aging even under conditions of reduced signal strength.

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Oancea, Romana, Vlad Bârsan, and Cristian Molder. "Perspective Correction For Image Processing." International conference KNOWLEDGE-BASED ORGANIZATION 21, no. 3 (June 1, 2015): 712–21. http://dx.doi.org/10.1515/kbo-2015-0120.

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Abstract The paper proposes an algorithm for applying the perspective correction of images containing human faces. Based on the coordinates of the two eyes, of the center of the mouth and of a point on the line of the mouth, one can estimate the angle of inclination of the face. After applying the perspective correction, the area corresponding to the face can be used by a face recognition algorithm based on aspect in order to improve the good recognition rate.

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Bentin, Shlomo, Yulia Golland, Anastasia Flevaris, Lynn C. Robertson, and Morris Moscovitch. "Processing the Trees and the Forest during Initial Stages of Face Perception: Electrophysiological Evidence." Journal of Cognitive Neuroscience 18, no. 8 (August 1, 2006): 1406–21. http://dx.doi.org/10.1162/jocn.2006.18.8.1406.

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Although configural processing is considered a hallmark of normal face perception in humans, there is ample evidence that processing face components also contributes to face recognition and identification. Indeed, most contemporary models posit a dual-code view in which face identification relies on the analysis of individual face components as well as the spatial relations between them. We explored the interplay between processing face configurations and inner face components by recording the N170, an event-related potential component that manifests early detection of faces. In contrast to a robust N170 effect elicited by line-drawn schematic faces compared to line-drawn schematic objects, no N170 effect was found if a pair of small objects substituted for the eyes in schematic faces. However, if a pair of two miniaturized faces substituted for the eyes, the N170 effect was restored. Additional experiments ruled out an explanation on the basis of miniaturized faces attracting attention independent of their location in a face-like configuration and show that global and local face characteristics compete for processing resources when in conflict. The results are discussed as they relate to normal and abnormal face processing.

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Blazhenkova, Olesya. "Boundary Extension in Face Processing." i-Perception 8, no. 5 (September 12, 2017): 204166951772480. http://dx.doi.org/10.1177/2041669517724808.

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Boundary extension is a common false memory error, in which people confidently remember seeing a wider angle view of the scene than was viewed. Previous research found that boundary extension is scene-specific and did not examine this phenomenon in nonscenes. The present research explored boundary extension in cropped face images. Participants completed either a short-term or a long-term condition of the task. During the encoding, they observed photographs of faces, cropped either in a forehead or in a chin area, and subsequently performed face recognition through a forced-choice selection. The recognition options represented different degrees of boundary extension and boundary restriction errors. Eye-tracking and performance data were collected. The results demonstrated boundary extension in both memory conditions. Furthermore, previous literature reported the asymmetry in amounts of expansion at different sides of an image. The present work provides the evidence of asymmetry in boundary extension. In the short-term condition, boundary extension errors were more pronounced for forehead, than for chin face areas. Finally, this research examined the relationships between the measures of boundary extension, imagery, and emotion. The results suggest that individual differences in emotional ability and object, but not spatial, imagery could be associated with boundary extension in face processing.

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Sreenivasan, Kartik K., Jonathan M. Goldstein, Audrey G. Lustig, Luis R. Rivas, and Amishi P. Jha. "Attention to faces modulates early face processing during low but not high face discriminability." Attention, Perception, & Psychophysics 71, no. 4 (May 2009): 837–46. http://dx.doi.org/10.3758/app.71.4.837.

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Parr, Lisa A., and Jessica Taubert. "The importance of surface-based cues for face discrimination in non-human primates." Proceedings of the Royal Society B: Biological Sciences 278, no. 1714 (December 2010): 1964–72. http://dx.doi.org/10.1098/rspb.2010.2333.

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Understanding how individual identity is processed from faces remains a complex problem. Contrast reversal, showing faces in photographic negative, impairs face recognition in humans and demonstrates the importance of surface-based information (shading and pigmentation) in face recognition. We tested the importance of contrast information for face encoding in chimpanzees and rhesus monkeys using a computerized face-matching task. Results showed that contrast reversal (positive to negative) selectively impaired face processing in these two species, although the impairment was greater for chimpanzees. Unlike chimpanzees, however, monkeys performed just as well matching negative to positive faces, suggesting that they retained some ability to extract identity information from negative faces. A control task showed that chimpanzees, but not rhesus monkeys, performed significantly better matching face parts compared with whole faces after a contrast reversal, suggesting that contrast reversal acts selectively on face processing, rather than general visual-processing mechanisms. These results confirm the importance of surface-based cues for face processing in chimpanzees and humans, while the results were less salient for rhesus monkeys. These findings make a significant contribution to understanding the evolution of cognitive specializations for face processing among primates, and suggest potential differences between monkeys and apes.

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Rennels, Jennifer L., Andrea J. Kayl, and Kirsty M. Kulhanek. "Individual Differences in Infants’ Temperament Affect Face Processing." Brain Sciences 10, no. 8 (July 23, 2020): 474. http://dx.doi.org/10.3390/brainsci10080474.

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Infants show an advantage in processing female and familiar race faces, but the effect sizes are often small, suggesting individual differences in their discrimination abilities. This research assessed whether differences in 6–10-month-olds’ temperament (surgency and orienting) predicted how they scanned individual faces varying in race and gender during familiarization and whether and how long it took them to locate the face during a visual search task. This study also examined whether infants viewing faces posing pleasant relative to neutral expressions would facilitate their discrimination of male and unfamiliar race faces. Results showed that infants’ surgency on its own or in conjunction with their orienting regularly interacted with facial characteristics to predict their scanning and location of faces. Furthermore, infants’ scanning patterns (dwell times and internal–external fixation shifts) correlated with their ability and time to locate a familiarized face. Moreover, infants who viewed faces with pleasant expressions showed better discrimination of unfamiliar race and male faces compared with infants who viewed neutral faces. Including temperament in the analyses consistently demonstrated its significance for understanding infant face processing. Findings suggest that positive interactions with other-race individuals and men might reduce processing disadvantages for those face types. Locating familiar adults in a timely manner is a crucial skill for infants to develop and these data elucidate factors influencing this ability.

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Lee, Jasmine K. W., Steve M. J. Janssen, and Alejandro J. Estudillo. "A featural account for own-face processing? Looking for support from face inversion, composite face, and part-whole tasks." i-Perception 13, no. 4 (July 2022): 204166952211114. http://dx.doi.org/10.1177/20416695221111409.

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It is widely accepted that face perception relies on holistic processing. However, this holistic advantage is not always found in the processing of the own face. Our study aimed to explore the role of holistic and featural processing in the identification of the own face, using three standard, but largely independent measures of holistic face processing: the face inversion task, the composite face task, and the part-whole task. Participants were asked to identify their face, a friend’s face, and an unfamiliar face in three different experimental blocks: (a) inverted versus upright; (b) top and bottom halves of the face aligned versus misaligned; and (c) facial features presented in isolation versus whole foil face context. Inverting a face impaired its identification, regardless of the identity. However, alignment effects were only found when identifying a friend or an unfamiliar face. In addition, a stronger feature advantage (i.e., better recognition for isolated features compared to in a whole-face context) was observed for the own face compared to the friend and unfamiliar faces. Altogether, these findings suggest that the own face is processed in a more featural manner but also relies on holistic processing. This work also highlights the importance of taking into consideration that different holistic processing paradigms could tap different forms of holistic processing.

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YAN, HONG. "HUMAN FACE IMAGE PROCESSING TECHNIQUES." International Journal of Image and Graphics 01, no. 02 (April 2001): 197–215. http://dx.doi.org/10.1142/s021946780100013x.

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Human face image processing techniques have many applications, such as in security operations, entertainment, medical imaging and telecommunications. In this paper, we provide an overview of existing computer algorithms for face detection and facial feature location, face recognition, image compression and animation. We also discuss limitations of current methods and research work needed in the future.

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CHEN, ZHENXUE, CHENGYUN LIU, FALIANG CHANG, XUZHEN HAN, and KAIFANG WANG. "ILLUMINATION PROCESSING IN FACE RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 05 (July 31, 2014): 1456011. http://dx.doi.org/10.1142/s0218001414560114.

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Changes in light intensity and angle present a major challenge to the creation of reliable face recognition systems. The existence of bright regions and dark regions has been shown to have a serious negative impact on the performance of face recognition systems. This paper proposes a solution to this problem based on self-quotient image (SQI) processing method. In this method, bright and dark areas are processed separately without changing the essential characteristics of the image of the face. The dark and light areas are processed separately by SQI. Experimental results indicate that this Single-Light-Region and Single-Dark-Region SQI method removes the adverse effect of multi-bright and multi-dark areas better than competing methods.

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Archer, Jacqueline, Dennis C. Hay, and Andrew W. Young. "Face processing in psychiatric conditions." British Journal of Clinical Psychology 31, no. 1 (February 1992): 45–61. http://dx.doi.org/10.1111/j.2044-8260.1992.tb00967.x.

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Rellecke, Julian, Arda Melih Bakirtas, Werner Sommer, and Annekathrin Schacht. "Automaticity in attractive face processing." NeuroReport 22, no. 14 (October 2011): 706–10. http://dx.doi.org/10.1097/wnr.0b013e32834a89ad.

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Martens, Ulla, Hartmut Leuthold, and Stefan R. Schweinberger. "Parallel processing in face perception." Journal of Experimental Psychology: Human Perception and Performance 36, no. 1 (2010): 103–21. http://dx.doi.org/10.1037/a0017167.

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Young, A. W. "Face processing impairments after amygdalotomy." Neurocase 3, no. 4 (August 1, 1997): 267k—274. http://dx.doi.org/10.1093/neucas/3.4.267-k.

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Morris, Richard W., Cynthia Shannon Weickert, and Carmel M. Loughland. "Emotional face processing in schizophrenia." Current Opinion in Psychiatry 22, no. 2 (March 2009): 140–46. http://dx.doi.org/10.1097/yco.0b013e328324f895.

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