Recognition memory for realistic synthetic faces

A series of experiments examined short-term recognition memory for trios of briefly presented, synthetic human faces derived from three real human faces. The stimuli were a graded series of faces, which differed by varying known amounts from the face of the average female. Faces based on each of the three real faces were transformed so as to lie along orthogonal axes in a 3-D face space. Experiment 1 showed that the synthetic faces' perceptual similarity structure strongly influenced recognition memory. Results were fit by a noisy exemplar model (NEMO) of perceptual recognition memory. The fits revealed thatrecognition memory was influenced both by the similarity of the probe to the series items and by the similarities among the series items themselves. Nonmetric multidimensional scaling (MDS) showed that the faces' perceptual representations largely preserved the 3-D space in which the face stimuli were arrayed. NEMO gave a better account of the results when similarity was defined as perceptual MDS similarity, rather than as the physical proximity of one face to another. Experiment 2 confirmed the importance of within-list homogeneity directly, without mediation of a model. We discuss the affinities and differences between visual memory for synthetic faces and memory for simpler stimuli.     

A multidimensional scaling analysis of own- and cross-race face spaces

We examined predictions derived from Valentine’s (1991) Multidimensional Space (MDS) framework for own- and other-race face processing. A set of 20 computerized faces was generated from a single prototype. Each face was saved as Black and White, changing only skin tone, such that structurally identical faces were represented in both race categories. Participants made speeded “same-different” judgments to all possible combinations of faces, from which we generated psychological spaces, with “different” RTs as the measure of similarity. Consistent with the MDS framework, all faces were pseudo-normally distributed around the (unseen) prototype. The distribution of faces was consistent with Valentine’s (1991) predictions: despite their physical identity to the White faces, Black faces had lower mean inter-object distances in psychological space. Other-race faces are more densely clustered in psychological space, which could underlie well-known recognition deficits.     

Physical and Psychological Representations of Faces: Evidence FromMorphing

Models of face recognition and classification often adopt a framework in which faces are represented as points in a multi-dimensional space. This psychological face space organizes the faces according to similarity and makes predictions for representational theories of faces. A variety of image-processing techniques have been used to create novel stimuli in this space that represent the average of a population or make a face appear more distinctive. The current research examined the relation between the stimuli created by these image-processing techniques and the underlying psychological representation as measured by multidimensional scaling (MDS) procedures. Morphing procedures were used to create 16 faces that were embedded in a set of 84 other faces. Similarity ratings between all possible pairs of faces were collected, and the data were analyzed using MDS procedures. Dimensions that emerged from the MDS solution included age, race, adiposity, and facial hair. In the MDS space, the morphs appeared more typical than the parents, as predicted by the geometric model. A number of biases were examined, including the tendency of the morphs to be less typical than predicted, which may be attributed to the effects of density near the center of face space. In addition, age and facial-adiposity biases were found. The results support the use of the face-space framework for models of face recognition, although image-processing techniques that are designed to create novel stimuli in this space may introduce systematic biases.     

Similarity-scaling studies of dot-pattern classification and recognition.

Classification performance in the dot-pattern, prototype-distortion paradigm (e.g., Posner & Keele, 1968) was modeled within a multidimensional scaling (MDS) framework. MDS solutions were derived for sets of dot patterns that were generated from prototypes. These MDS solutions were then used in conjunction with exemplar, prototype, and combined models to predict classification and recognition performance. Across 3 experiments, an MDS-based exemplar model accounted for the effects of several fundamental learning variables, including level of distortion of the patterns, category size, delay of transfer phase, and item frequency. Most important, the model quantitatively predicted classification probabilities for individual dot patterns in the sets, not simply general trends of performance. There was little evidence for the existence of a prototype-abstraction process that operated above and beyond pure exemplar-based generalization.     

Predicting similarity and categorization from identification.

In this article, the relation between the identification, similarity judgment, and categorization of multidimensional perceptual stimuli is studied. The theoretical analysis focused on general recognition theory (GRT), which is a multidimensional generalization of signal detection theory. In one application, 2 Ss first identified a set of confusable stimuli and then made judgments of their pairwise similarity. The second application was to Nosofsky's (1985b, 1986) identification-categorization experiment. In both applications, a GRT model accounted for the identification data better than Luce's (1963) biased-choice model. The identification results were then used to predict performance in the similarity judgment and categorization conditions. The GRT identification model accurately predicted the similarity judgments under the assumption that Ss allocated attention to the 2 stimulus dimensions differently in the 2 tasks. The categorization data were predicted successfully without appealing to the notion of selective attention. Instead, a simpler GRT model that emphasized the different decision rules used in identification and categorization was adequate.     

Second-order isomorphism of internal representations of familiar faces

Following a suggestion by Shepard and Chipman (1970), photographs and names of 15 well-known faces were used as stimuli in judgments of similarity. Ss ranked all pairs of stimuli in terms of facial similarity either from memory when presented with pairs of names, or from photographs. There was a highly significant positive correlation between these two types of judgment. A simple classificatory analysis of the 15 faces in terms of the physical features provided evidence that judgments based on the internal representation of the faces utilized pictorial information. These results extend the generality of Shepard and Chipman’s findings and confirm the usefulness of an approach to the problem of mental images based on the concept of second-order isomorphism.     

Exploring children’s face-space: A multidimensional scaling analysis of the mental representation of facial identity

We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an “odd-man-out” paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces in a multidimensional space. Five dimensions accounted optimally for the judgments of both children and adults, with similar local clustering of faces. However, the fit of the MDS solutions was better for adults, in part because children’s responses were more variable. More children relied predominantly on a single dimension, namely eye color, whereas adults appeared to use multiple dimensions for each judgment. The pattern of findings suggests that children’s mental representation of faces has a structure similar to that of adults but that children’s judgments are influenced less consistently by that overall structure.     

How similar are recognition memory and inductive reasoning?

Conventionally, memory and reasoning are seen as different types of cognitive activities driven by different processes. In two experiments, we challenged this view by examining the relationship between recognition memory and inductive reasoning involving multiple forms of similarity. A common study set (members of a conjunctive category) was followed by a test set containing old and new category members, as well as items that matched the study set on only one dimension. The study and test sets were presented under recognition or induction instructions. In Experiments 1 and 2, the inductive property being generalized was varied in order to direct attention to different dimensions of similarity. When there was no time pressure on decisions, patterns of positive responding were strongly affected by property type, indicating that different types of similarity were driving recognition and induction. By comparison, speeded judgments showed weaker property effects and could be explained by generalization based on overall similarity. An exemplar model, GEN-EX (GENeralization from EXamples), could account for both the induction and recognition data. These findings show that induction and recognition share core component processes, even when the tasks involve flexible forms of similarity.     

Further tests of an exemplar-similarity approach to relating identification and categorization

Further tests were provided of an exemplar-similarity model for relating the identification and categorization of separable-dimension stimuli (Nosofsky, 1986). On the basis of confusion errors in an identification paradigm, a multidimensional scaling (MDS) solution was derived for a set of 16 separable-dimension stimuli. This MDS solution was then used in conjunction with the exemplar-similarity model to accurately predict performance in four separate categorization paradigms with the same stimuli. A key to achieving the accurate quantitative fits was the assumption that a selective attention process systematically modifies similarities among exemplars across different category structures. The tests reported go well beyond earlier ones (Nosofsky, 1986) in demonstrating the generalizability and utility of the theoretical approach. Implications of the results for alternative quantitative models of classification performance, including Ashby and Perrin's (1988) general recognition theory, were also considered.     

Classification in well-defined and ill-defined categories: evidence for common processing strategies

Early work in perceptual and conceptual categorization assumed that categories had criterial features and that category membership could be determined by logical rules for the combination of features. More recent theories have assumed that categories have an ill-defined structure and have prosposed probabilistic or global similarity models for the verification of category membership. In the experiments reported here, several models of categorization were compared, using one set of categories having criterial features and another set having an ill-defined structure. Schematic faces were used as exemplars in both cases. Because many models depend on distance in a multidimensional space for their predictions, in Experiment 1 a multidimensional scaling study was performed using the faces of both sets as stimuli, In Experiment 2, subjects learned the category membership of faces for the categories having criterial features. After learning, reaction times for category verification and typicality judgments were obtained. Subjects also judged the similarity of pairs of faces. Since these categories had characteristic as well as defining features, it was possible to test the predictions of the feature comparison model (Smith et al.), which asserts that reaction times and typicalities are affected by characteristic features. Only weak support for this model was obtained. Instead, it appeared that subjects developed logical rules for the classification of faces. A characteristic feature affected reaction times only when it was part of the rule system devised by the subject. The procedure for Experiment 3 was like that for Experiment 2, but with ill-defined rather than well-defined categories. The obtained reaction times had high correlations with some of the models for ill-defined categories. However, subjects' performance could best be described as one of feature testing based on a logical rule system for classification. These experiments indicate that whether or not categories have criterial features, subjects attempt to develop a set of feature tests that allow for exemplar classification. Previous evidence supporting probabilistic or similarity models may be interpreted as resulting from subjects' use of the most efficient rules for classification and the averaging of responses for subjects using different sets of rules.     

Using ecphoric confidence ratings to discriminate seen from unseen faces: The effects of retention interval and distinctiveness

Theories of confidence processing for recognition judgments suggest that confidence indexes the degree of match between a presented stimulus and an image in memory (ecphoric similarity). Recent research has demonstrated that having participants rate their confidence that a face had been previously seen provides an equivalent or a better index of the stimulus's status than does eliciting a simple binary response (Sauer, Brewer, & Weber, Journal of Experimental Psychology: General 137: 528-547, 2008). Using a face recognition paradigm, we manipulated retention interval and stimulus distinctiveness to directly test the suggestion that confidence indexes ecphoric similarity and to probe the boundary conditions for using confidence ratings to discriminate seen from unseen faces. Consistent with the proposed ecphoric basis for confidence ratings, mean confidence was higher for previously seen than for unseen faces, and conditions conducive to the formation of strong memories improved confidence-based discrimination. In all conditions, after the application of a classification algorithm, confidence ratings provided a more sensitive index of face status (i.e., seen or unseen) than did binary responses.     

An exemplar-retrieval model of speeded same--different judgments

R. M. Nosofsky and T. J. Palmeri's (1997) exemplar-based random-walk (EBRW) model of speeded classification is extended to account for speeded same--different judgments among integral-dimension stimuli. According to the model, an important component process of same--different judgments is that people store individual examples of experienced same and different pairs of objects in memory. These exemplar pairs are retrieved from memory on the basis of how similar they are to a currently presented pair of objects. The retrieved pairs drive a random-walk process for making same--different decisions. The EBRW predicts correctly that same responses are faster for objects lying in isolated than in dense regions of similarity space. The model also predicts correctly effects of same-identity versus same-category instructions and is sensitive to observers' past experiences with specific same and different pairs of objects.     

Dissimilarities as indices of individual perceptual structure

The generality of dissimilarity judgments and of configurations obtained by multidimensional scaling (MDS) as indices of perceptual structure was examined. The Ss made magnitude estimates of dissimilarity of pairs of photos, and MDS configurations were constructed separately for each S. The compatability of dissimilarities (judgments or distances in MDS configurations) with two other tasks Ss performed was then examined. These additional tasks, an “encoding” and a “decoding” task, required the S to first construct a message by making use of a set of four photos and, a week later, to decode the messages. Results obtained were interpreted as indicating a degree of generality of the dissimilarities and supporting a hypothesis of individual differences in perceptual structure for the stimulus set. A “data-purification” hypothesis for MDS was discussed and examined.

     

Recognizing distinctive faces: A hybrid-similarity exemplar model account

In recognition memory experiments, Nosofsky and Zaki (2003) found that adding discrete distinctive features to continuous-dimension color stimuli helped participants to identify old items as old (the old-item distinctiveness effect), as well as to identify new items as new. The present study tests the extent to which these results generalize to the domain of face recognition. Two experiments were conducted, one using artificial faces and one using natural faces. Artificial faces were used to test memory for faces with discrete distinctive features while controlling the similarity of the faces themselves on more continuous dimensions. The natural-face experiment used the faces of 40 bald men categorized into three groups (typical, isolated, and distinctive) based on experimental ratings of distinctiveness. In both experiments, there were strong effects of the distinctive features on recognition performance. The data were accounted for reasonably well by a hybrid-similarity version of an exemplar recognition model (Nosofsky and Zaki, 2003), which includes a feature-matching mechanism that can provide boosts to an item's self-similarity.     

面孔部件相似性判断研究

用Morph变形方法构建家族相似性面孔部件样例,采用多级估量法探讨分类活动中面孔部件相似性判断问题。结果发现,部件样例对部件原型的隶属度及部件样例对整体原型中对应部件的隶属度与部件样例变形百分比间是3次函数关系;耳朵、脸型、眼睛等部件样例对整体原型中对应部件的隶属度小于其对部件原型的隶属度,嘴巴样例对整体原型中嘴巴部件的隶属度高于其对部件原型的隶属度。表明面孔部件物理相似性与心理相似性间是3次函数关系;整体原型中其他部件降低了耳朵、脸型、眼睛等部件样例对整体原型中对应部件的隶属度,而提高了嘴巴样例对整体原     

Attention and learning processes in the identification and categorization of integral stimuli

The relationship between subjects' identification and categorization learning of integral-dimension stimuli was studied within the framework of an exemplar-based generalization model. The model was used to predict subjects' learning in six different categorization conditions on the basis of data obtained in a single identification learning condition. A crucial assumption in the model is that because of selective attention to component dimensions, similarity relations may change in systematic ways across different experimental contexts. The theoretical analysis provided evidence that, at least under unspeeded conditions, selective attention may play a critical role in determining the identification-categorization relationship for integral stimuli. Evidence was also provided that similarity among exemplars decreased as a function of identification learning. Various alternative classification models, including prototype, multiple-prototype, average distance, and "value-on-dimensions" models, were unable to account for the results.     

Similarity and categorization of environmental sounds

Four experiments investigated the acoustical correlates of similarity and categorization judgments of environmental sounds. In Experiment 1, similarity ratings were obtained from pairwise comparisons of recordings of 50 environmental sounds. A three-dimensional multidimensional scaling (MDS) solution showed three distinct clusterings of the sounds, which included harmonic sounds, discrete impact sounds, and continuous sounds. Furthermore, sounds from similar sources tended to be in close proximity to each other in the MDS space. The orderings of the sounds on the individual dimensions of the solution were well predicted by linear combinations of acoustic variables, such as harmonicity, amount of silence, and modulation depth. The orderings of sounds also correlated significantly with MDS solutions for similarity ratings of imagined sounds and for imagined sources of sounds, obtained in Experiments 2 and 3--as was the case for free categorization of the 50 sounds (Experiment 4)--although the categorization data were less well predicted by acoustic features than were the similarity data.