Further experiments on the perception of growth in three dimensions

Bruce, Vicki; Burton, A. Mike; Doyle, Tony; Dench, Neal

doi:10.3758/bf03208149

Cited by 39 publications

(23 citation statements)

References 17 publications

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“…If subjects are forced to use only one cue because only one is available (such as cardioidal strain or skin texture) it is still possible for them to make reasonably accurate age judgments but, in practice, cues to age are probably normally used in combination. This reinforces the conclusions drawn by Bruce et al (1989), who found that providing subjects with a richer database on which to base their age judgments (computer-generated 3-D head models) led to poorer and more idiosyncratic performance than that found by Mark and Todd (1985) who used simple line drawings of head profiles.…”

Section: Discussionsupporting

confidence: 70%

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Factors Influencing the Accuracy of Age Estimates of Unfamiliar Faces

1995

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Abstract. Factors affecting the accuracy with which adults could assess the age of unfamiliar male faces aged between 5 and 70 years were examined. In the first experiment twenty-five 'young' adult subjects, aged 16-25, and twenty-five 'old' adults, aged 51-60, were used. Each subject saw five versions of three different faces: these consisted of an original version of each face and four manipulated versions of it. The manipulations consisted of mirror reversal, pseudo-cardioidal strain, thresholding, and elimination of all but the internal features of the face. The second experiment was similar except that a between-subjects design was used: each subject saw three faces for each age category of target face, but was exposed to only a single type of manipulation (plus a set of 'original' faces which were identical for all groups, so that the comparability of the different groups in age estimation could be checked).Results from both experiments were similar. Age estimates for unmanipulated 'original' faces were highly accurate, although subjects were most accurate with target faces that were within their own age range. Results for the manipulated faces implied that the importance of cardioidal strain as a necessary and sufficient cue to age may have been overestimated in previous reports: subjects' age estimates were accurate when cardioidal strain was absent from the stimulus, and poor when cardioidal strain was the only cue available.

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Section: Discussionsupporting

confidence: 70%

“…For example, Mark and Todd (1985) and Bruce et al (1989) obtained their data by presenting subjects with stimuli in pairs and asking them to decide which of each pair looked 'older'. Measures like this provide information about relative-age judgments, but would have been too crude for our purposes.…”

Section: Discussionmentioning

confidence: 99%

Factors Influencing the Accuracy of Age Estimates of Unfamiliar Faces

1995

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“…Pittenger, Shaw, Mark, and their colleagues (eg Pittenger and Shaw 1975;Pittenger et al 1979;Mark and Todd 1985; see also Bruce et al 1989) have shown that changes in the shape of the skull during growth can be modelled by a mathematical transformation called cardioidal strain. These researchers suggest that sensitivity to the level of cardioidal strain underlies judgments of facial age.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Feature-Based Information in the Age Processing of Unfamiliar Faces

George

Hole

1998

Perception

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The influence of the internal features (eyes, nose, and mouth) in the age processing of unfamiliar faces was examined. Younger and older versions of the faces of six individuals (covering three different age ranges, from infancy to maturity) were used as donor stimuli. For each individual in turn, the effects on age estimates of placing older features in the younger face version (or vice versa) were investigated. Age estimates were heavily influenced by the age of the internal facial features. Experiment 2 replicated these effects with a larger number of faces within a narrower age range (after growth is complete and before major skin changes have occurred). Taken together, these two experiments show that the internal facial features may be influential in conveying age information to the perceiver. However, the mechanisms by which features exert their influence remain difficult to determine: although age estimates might be based on local information from the features themselves, an alternative possibility is that featural changes indirectly influence age estimates by altering the global three-dimensional shape of the head.

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“…D'Arcy Thompson [6] suggested that it is possible to use co-ordinate transformations for altering the shape of biological organisms in order to produce shapes belonging to different but similar biological organisms. Based on this idea a number of researchers [1,19,20] investigated the use of co-ordinate transformations in an attempt to impose age-related changes on human faces. According to their experimental evaluations the perceived age of transformed facial outlines can be altered according to the transformation factors used.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparing Different Classifiers for Automatic Age Estimation

Lanitis¹,

Draganova

Christodoulou

2004

IEEE Trans. Syst., Man, Cybern. B

517

320

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We describe a quantitative evaluation of the performance of different classifiers in the task of automatic age estimation. In this context we generate a statistical model of facial appearance, which is subsequently used as the basis for obtaining a compact parametric description of face images. The aim of our work is to design classifiers that accept the model-based representation of unseen images and produce an estimate of the age of the person in the corresponding face image. For this application we have tested different classifiers: a classifier based on the use of quadratic functions for modeling the relationship between face model parameters and age, a shortest distance classifier and artificial neural network based classifiers. We also describe variations to the basic method where we use age-specific and/or appearance specific age estimation methods. In this context we use age estimation classifiers for each age group and/or classifiers for different clusters of subjects within our training set. In those cases part of the classification procedure is devoted to choosing the most appropriate classifier for the subject/age range in question, so that more accurate age estimates can be obtained. We also present comparative results concerning the performance of humans 1 and computers in the task of age estimation. Our results indicate that machines can estimate the age of a person almost as reliably as humans.

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Further experiments on the perception of growth in three dimensions

Cited by 39 publications

References 17 publications

Factors Influencing the Accuracy of Age Estimates of Unfamiliar Faces

Factors Influencing the Accuracy of Age Estimates of Unfamiliar Faces

The Influence of Feature-Based Information in the Age Processing of Unfamiliar Faces

Comparing Different Classifiers for Automatic Age Estimation

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