A Goal-Oriented Model for Rehabilitation of Adult Deaf Persons

Non

A Pilot Investigation of Three Factors of the 16 P.F. Form E Comparing the Standard Written Form with an Ameslan Videotape Revision

non

Mate choice, mate preference, and biological markets : the relationship between partner choice and health preference is modulated by women's own attractiveness

Although much of the research on human mate preference assumes that mate preference and partner choice will be related to some extent, evidence for correlations between mate preference and mate choice is mixed. Inspired by biological market theories of mate choice, which propose that individuals with greater market value will be better placed to translate their preference into choice, we investigated whether participants' own attractiveness modulated the relationship between their preference and choice. Multilevel modeling showed that experimentally assessed preferences for healthy-looking other-sex faces predicted third-party ratings of partner's facial health better among women whose faces were rated as more attractive by third parties. This pattern of results was not seen for men. These results suggest that the relationship between mate preference and mate choice may be more complex than was assumed in previous research, at least among women. Our results also highlight the utility of biological market theories for understanding the links between mate preference and partner choice

A database of whole-body action videos for the study of action, emotion, and untrustworthiness

We present a database of high-definition (HD) videos for the study of traits inferred from whole-body actions. Twenty-nine actors (19 female) were filmed performing different actions—walking, picking up a box, putting down a box, jumping, sitting down, and standing and acting—while conveying different traits, including four emotions (anger, fear, happiness, sadness), untrustworthiness, and neutral, where no specific trait was conveyed. For the actions conveying the four emotions and untrustworthiness, the actions were filmed multiple times, with the actor conveying the traits with different levels of intensity. In total, we made 2,783 action videos (in both two-dimensional and three-dimensional format), each lasting 7 s with a frame rate of 50 fps. All videos were filmed in a green-screen studio in order to isolate the action information from all contextual detail and to provide a flexible stimulus set for future use. In order to validate the traits conveyed by each action, we asked participants to rate each of the actions corresponding to the trait that the actor portrayed in the two-dimensional videos. To provide a useful database of stimuli of multiple actions conveying multiple traits, each video name contains information on the gender of the actor, the action executed, the trait conveyed, and the rating of its perceived intensity. All videos can be downloaded free at the following address: http://www-users.york.ac.uk/~neb506/databases.html. We discuss potential uses for the database in the analysis of the perception of whole-body actions

Human Centric Facial Expression Recognition

Facial expression recognition (FER) is an area of active research, both in computer science and in behavioural science. Across these domains there is evidence to suggest that humans and machines find it easier to recognise certain emotions, for example happiness, in comparison to others. Recent behavioural studies have explored human perceptions of emotion further, by evaluating the relative contribution of features in the face when evaluating human sensitivity to emotion. It has been identified that certain facial regions have more salient features for certain expressions of emotion, especially when emotions are subtle in nature. For example, it is easier to detect fearful expressions when the eyes are expressive. Using this observation as a starting point for analysis, we similarly examine the effectiveness with which knowledge of facial feature saliency may be integrated into current approaches to automated FER. Specifically, we compare and evaluate the accuracy of ‘full-face’ versus upper and lower facial area convolutional neural network (CNN) modelling for emotion recognition in static images, and propose a human centric CNN hierarchy which uses regional image inputs to leverage current understanding of how humans recognise emotions across the face. Evaluations using the CK+ dataset demonstrate that our hierarchy can enhance classification accuracy in comparison to individual CNN architectures, achieving overall true positive classification in 93.3% of cases

No compelling evidence that preferences for facial masculinity track changes in women’s hormonal status

Although widely cited as strong evidence that sexual selection has shaped human facial-attractiveness judgments, findings suggesting that women’s preferences for masculine characteristics in men’s faces are related to women’s hormonal status are equivocal and controversial. Consequently, we conducted the largest-ever longitudinal study of the hormonal correlates of women’s preferences for facial masculinity (N = 584). Analyses showed no compelling evidence that preferences for facial masculinity were related to changes in women’s salivary steroid hormone levels. Furthermore, both within-subjects and between-subjects comparisons showed no evidence that oral contraceptive use decreased masculinity preferences. However, women generally preferred masculinized over feminized versions of men’s faces, particularly when assessing men’s attractiveness for short-term, rather than long-term, relationships. Our results do not support the hypothesized link between women’s preferences for facial masculinity and their hormonal status

A Goal-Oriented Model for Rehabilitation of Adult Deaf Persons

Non

A Pilot Investigation of Three Factors of the 16 P.F. Form E Comparing the Standard Written Form with an Ameslan Videotape Revision

non