A computer-generated face database with ratings on realism, masculinity, race, and stereotypy

Matheson, Heath E.; McMullen, Patricia A.

doi:10.3758/s13428-010-0029-9

Cited by 19 publications

(23 citation statements)

References 8 publications

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“…Further, each face in the database is associated with ratings of stereotypy and a categorical rating of face-race, demonstrating that participants are aware that the faces are of different ethnicities. These findings increase the confidence that these faces were processed in a way similar to real, photographic, images (see Matheson & McMullen, 2011).…”

Section: Stimulimentioning

confidence: 71%

Second-order relational face processing is applied to faces of different race and photographic contrast.

Matheson¹,

Bilsbury²,

McMullen³

2012

Canadian Journal of Experimental Psychology / Revue canadienne

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A large body of research suggests that faces are processed by a specialized mechanism within the human visual system. This specialized mechanism is made up of subprocesses (Maurer, LeGrand, & Mondloch, 2002). One subprocess, called second- order relational processing, analyzes the metric distances between face parts. Importantly, it is well established that other-race faces and contrast-reversed faces are associated with impaired performance on numerous face processing tasks. Here, we investigated the specificity of second-order relational processing by testing how this process is applied to faces of different race and photographic contrast. Participants completed a feature displacement discrimination task, directly measuring the sensitivity to second-order relations between face parts. Across three experiments we show that, despite absolute differences in sensitivity in some conditions, inversion impaired performance in all conditions. The presence of robust inversion effects for all faces suggests that second-order relational processing can be applied to faces of different race and photographic contrast.

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Section: Stimulimentioning

confidence: 71%

Second-order relational face processing is applied to faces of different race and photographic contrast.

Matheson¹,

Bilsbury²,

McMullen³

2012

Canadian Journal of Experimental Psychology / Revue canadienne

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“…This simple fact has translated to the extensive use of face stimuli in psychological research. Fortunately, researchers have many options for facial stimuli at their disposal, ranging from published databases (e.g., Ekman & Friesen, 1976;Lundqvist et al, 1998;Tottenham et al, 2009), to archives (e.g., Blair et al, 2004;Pauker & Ambady, 2009), to artificial faces (e.g., Matheson & McMullen, 2011), each of which has merits as well as drawbacks. This paper describes the development of a new database of facial stimuli and accompanying data including subjective ratings from a large sample and objective measures.…”

Section: Discussionmentioning

confidence: 99%

“…A third type of databases is comprised of artificial faces (e.g., Matheson & McMullen, 2011). These faces can be computer generated using software programs, morphed from real faces, or sketched.…”

Section: Existing Databasesmentioning

confidence: 99%

The Chicago face database: A free stimulus set of faces and norming data

2015

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Researchers studying a range of psychological phenomena (e.g., theory of mind, emotion, stereotyping and prejudice, interpersonal attraction, etc.) sometimes employ photographs of people as stimuli. In this paper, we introduce the Chicago Face Database, a free resource consisting of 158 high-resolution, standardized photographs of Black and White males and females between the ages of 18 and 40 years and extensive data about these targets. In Study 1, we report pretesting of these faces, which includes both subjective norming data and objective physical measurements of the images included in the database. In Study 2 we surveyed psychology researchers to assess the suitability of these targets for research purposes and explored factors that were associated with researchers' judgments of suitability. Instructions are outlined for those interested in obtaining access to the stimulus set and accompanying ratings and measures.

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“…FaceGen uses the approach described in Blanz & Vetter (1999) to parameterize and generate three-dimensional faces of varying age, race, and gender; similar faces are currently used in another recently published stimulus set of faces (Matheson & McMullen, 2011). These faces were then exported as polygon meshes, collections of connected points in a three-dimensional space that represent the shape of the face and head.…”

Section: Stimuli Descriptionmentioning

confidence: 99%

“…Computer-generated faces show comparable results to real faces in behavioral and EEG research (Balas & Nelson, 2010; Freeman, Pauker, Apfelbaum, & Ambady, 2010; Lindsen, Jones, Shimojo, & Bhattacharya, 2010), and a recently released database of static computer-generated faces was used to replicate experimental findings of other-race and face inversion effects (Matheson & McMullen, 2011). The stimulus set we present here is a novel contribution to the field, addressing two currently unmet needs by (1) introducing movement and (2) contributing both emotional and non-emotional facial movements and poses while controlling for luminance, movement speed, size, and quality of expression.…”

mentioning

confidence: 99%

A computer-generated animated face stimulus set for psychophysiological research

et al. 2014

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Human faces are fundamentally dynamic, but experimental investigations of face perception traditionally rely on static images of faces. While naturalistic videos of actors have been used with success in some contexts, much research in neuroscience and psychophysics demands carefully controlled stimuli. In this paper, we describe a novel set of computer generated, dynamic, face stimuli. These grayscale faces are tightly controlled for low- and high-level visual properties. All faces are standardized in terms of size, luminance, and location and size of facial features. Each face begins with a neutral pose and transitions to an expression over the course of 30 frames. Altogether there are 222 stimuli spanning 3 different categories of movement: (1) an affective movement (fearful face); (2) a neutral movement (close-lipped, puffed cheeks with open eyes); and (3) a biologically impossible movement (upward dislocation of eyes and mouth). To determine whether early brain responses sensitive to low-level visual features differed between expressions, we measured the occipital P100 event related potential (ERP), which is known to reflect differences in early stages of visual processing and the N170, which reflects structural encoding of faces. We found no differences between faces at the P100, indicating that different face categories were well matched on low-level image properties. This database provides researchers with a well-controlled set of dynamic faces controlled on low-level image characteristics that are applicable to a range of research questions in social perception.

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A computer-generated face database with ratings on realism, masculinity, race, and stereotypy

Cited by 19 publications

References 8 publications

Second-order relational face processing is applied to faces of different race and photographic contrast.

Second-order relational face processing is applied to faces of different race and photographic contrast.

The Chicago face database: A free stimulus set of faces and norming data

A computer-generated animated face stimulus set for psychophysiological research

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