Judgments of Height From Faces are Informed by Dominance and Facial Maturity

Burton, Caitlin M.; Rule, Nicholas O.

doi:10.1521/soco.2013.31.6.672

Cited by 12 publications

(13 citation statements)

References 27 publications

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“…Medical studies suggest that the height of an individual can be approximated given ratios of limb proportions [1], absolute tibia length [11], foot length [46], and the ratio of head to shoulders [19,37]. Also human perception of height seems influenced by head to shoulders ratio, which suggests a real link between head to shoulders ratio to actual height [5,27,33]. There is also a body of anthropological research about inferring the living height of the individual from the length of several bones in their skeletons, which indicates that height can be approximated given the size of some body parts [2,11,44].…”

Section: Related Workmentioning

confidence: 99%

“…It may be distributed unchanged freely in print or electronic forms. arXiv:1805.10355v1 [cs.CV] 25 May 2018 parts [1,2,5,11,19,27,33,37,44,46], such as the ratio of the tibia length to the whole body or the head to shoulders ratio, which are scale invariant. To this end, we train Deep Nets to capture the correlation between the relative size of body parts without having to explicitly measure them.…”

Section: Introductionmentioning

confidence: 99%

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What Face and Body Shapes Can Tell Us About Height

Günel

Rhodin

Fua

2019

2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)

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Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance, however, it is also very challenging due to the absence of absolute scale information. We tackle the rarely addressed case, where camera parameters and scene geometry is unknown. To nevertheless resolve the inherent scale ambiguity, we infer height from statistics that are intrinsic to human anatomy and can be estimated from images directly, such as articulated pose, bone-length proportions, and facial features. Our contribution is twofold. First, we experiment with different machine learning models to capture the relation between image content and human height. Second, we show that performance is predominantly limited by dataset size and create a new dataset that is three magnitudes larger, by mining explicit height labels and propagating them to additional images through face recognition and assignment consistency. Our evaluation shows that monocular height estimation is possible with a MAE of 5.56cm.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

What Face and Body Shapes Can Tell Us About Height

Günel

Rhodin

Fua

2019

2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)

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“…There are also studies exploring the perception of physical characteristics from both face and voice cues (Puts, Jones, & Debruine, 2012;Re, DeBruine, Jones, & Perrett, 2013). Some studies show that both visual and acoustic characteristics are highly correlated with measures of a person's strength, height and weight (Burton & Rule, 2013;Hodges-Simeon, Gurven, Puts, & Gaulin, 2014), while others report First impressions from faces and voices high correlations between face-and voice-based ratings for masculinity, health and height (Smith, Dunn, Baguley, & Stacey, 2016). Together with findings of the strong relationship between facial and vocal perceived threat (Han et al, 2017), these studies suggest a possible link between dominance judgements inferred from the face and the voice.…”

Section: Introductionmentioning

confidence: 99%

The Role of Face and Voice Cues in Predicting the Outcome of Student Representative Elections

Mileva

Tompkinson

Watt

et al. 2019

Pers Soc Psychol Bull

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First impressions formed after seeing someone’s face or hearing their voice can affect many social decisions, including voting in political elections. Despite the many studies investigating the independent contribution of face and voice cues to electoral success, their integration is still not well understood. Here, we examine a novel electoral context, student representative ballots, allowing us to test the generalizability of previous studies. We also examine the independent contributions of visual, auditory, and audiovisual information to social judgments of the candidates, and their relationship to election outcomes. Results showed that perceived trustworthiness was the only trait significantly related to election success. These findings contrast with previous reports on the importance of perceived competence using audio or visual cues only in the context of national political elections. The present study highlights the role of real-world context and emphasizes the importance of using ecologically valid stimulus presentation in understanding real-life social judgment.

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“…Other psychological experiments in lab settings have tried to explain the aforementioned biases by constructing mental models for how people judge weight and height. Facial adiposity [4] was found to constitute an important signal used in weight estimation, whereas features such as dominance and facial maturity [5], as well as head-to-shoulder ratio [18], are prominent in height estimation. Robinson [7] proposed visual normalization theory, a framework for explaining why people under-or overestimate certain body shapes.…”

Section: Related Workmentioning

confidence: 99%

“…In terms of action, understanding human perception of body measurements should therefore play a critical role for public health agencies when striving to design effective strategies for raising awareness about the prevalence and risks of overweight and obesity. For all these reasons, the estimation of human body measurements is an active area of interest in medical research [2,[4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Human biases in body measurement estimation

Martynov¹,

Garimella

West

2020

EPJ Data Sci.

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Body measurements, including weight and height, are key indicators of health. Being able to visually assess body measurements reliably is a step towards increased awareness of overweight and obesity and is thus important for public health. Nevertheless it is currently not well understood how accurately humans can assess weight and height from images, and when and how they fail. To bridge this gap, we start from 1,682 images of persons collected from the Web, each annotated with the true weight and height, and ask crowd workers to estimate the weight and height for each image. We conduct a faceted analysis taking into account characteristics of the images as well as the crowd workers assessing the images, revealing several novel findings: (1) Even after aggregation, the crowd’s accuracy is overall low. (2) We find strong evidence of contraction bias toward a reference value, such that the weight of light people and the height of short people are overestimated, whereas the weight of heavy people and the height of tall people are underestimated. (3) We estimate workers’ individual reference values using a Bayesian model, finding that reference values strongly correlate with workers’ own height and weight, indicating that workers are better at estimating people similar to themselves. (4) The weight of tall people is underestimated more than that of short people; yet, knowing the height decreases the weight error only mildly. (5) Accuracy is higher on images of females than of males, but female and male workers are no different in terms of accuracy. (6) Crowd workers improve over time if given feedback on previous guesses. Finally, we explore various bias correction models for improving the crowd’s accuracy, but find that this only leads to modest gains. Overall, this work provides important insights on biases in body measurement estimation as obesity-related conditions are on the rise.

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Judgments of Height From Faces are Informed by Dominance and Facial Maturity

Cited by 12 publications

References 27 publications

What Face and Body Shapes Can Tell Us About Height

What Face and Body Shapes Can Tell Us About Height

The Role of Face and Voice Cues in Predicting the Outcome of Student Representative Elections

Human biases in body measurement estimation

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