Distinguishing Posed and Spontaneous Smiles by Facial Dynamics

Smile is one of the key elements in identifying emotions and present state of mind of an individual. In this work, we propose a cluster of approaches to classify posed and spontaneous smiles using deep convolutional neural network (CNN) face features, local phase quantization (LPQ), dense optical flow and histogram of gradient (HOG). Eulerian Video Magnification (EVM) is used for micro-expression smile amplification along with three normalization procedures for distinguishing posed and spontaneous smiles. Although the deep CNN face model is trained with large number of face images, HOG features outperforms this model for overall face smile classification task. Using EVM to amplify micro-expressions did not have a significant impact on classification accuracy, while the normalizing facial features improved classification accuracy. Unlike many manual or semi-automatic methodologies, our approach aims to automatically classify all smiles into either `spontaneous' or `posed' categories, by using support vector machines (SVM). Experimental results on large UvA-NEMO smile database show promising results as compared to other relevant methods.Comment: 16 pages, 8 figures, ACCV 2016, Second Workshop on Spontaneous Facial Behavior Analysi

Extended Calculations of Spectroscopic Data: Energy Levels, Lifetimes and Transition rates for O-like ions from Cr XVII to Zn XXIII

Employing two state-of-the-art methods, multiconfiguration Dirac--Hartree--Fock and second-order many-body perturbation theory, the excitation energies and lifetimes for the lowest 200 states of the $2s^2 2p^4$, $2s 2p^5$, $2p^6$, $2s^2 2p^3 3s$, $2s^2 2p^3 3p$, $2s^2 2p^3 3d$, $2s 2p^4 3s$, $2s 2p^4 3p$, and $2s 2p^4 3d$ configurations, and multipole (electric dipole (E1), magnetic dipole (M1), and electric quadrupole (E2)) transition rates, line strengths, and oscillator strengths among these states are calculated for each O-like ion from Cr XVII to Zn XXIII. Our two data sets are compared with the NIST and CHIANTI compiled values, and previous calculations. The data are accurate enough for identification and deblending of new emission lines from the sun and other astrophysical sources. The amount of data of high accuracy is significantly increased for the $n = 3$ states of several O-like ions of astrophysics interest, where experimental data are very scarce

Seasonal variation of aerosol water uptake and its impact on the direct radiative effect at Ny-Ålesund, Svalbard

© Author(s) 2014. This work is distributed under the Creative Commons Attribution 3.0 LicenseIn this study we investigated the impact of water uptake by aerosol particles in ambient atmosphere on their optical properties and their direct radiative effect (ADRE, W m-2) in the Arctic at Ny-Ålesund, Svalbard, during 2008. To achieve this, we combined three models, a hygroscopic growth model, a Mie model and a radiative transfer model, with an extensive set of observational data. We found that the seasonal variation of dry aerosol scattering coefficients showed minimum values during the summer season and the beginning of fall (July-August-September), when small particles (< 100 nm in diameter) dominate the aerosol number size distribution. The maximum scattering by dry particles was observed during the Arctic haze period (March-April-May) when the average size of the particles was larger. Considering the hygroscopic growth of aerosol particles in the ambient atmosphere had a significant impact on the aerosol scattering coefficients: the aerosol scattering coefficients were enhanced by on average a factor of 4.30 ± 2.26 (mean ± standard deviation), with lower values during the haze period (March-April-May) as compared to summer and fall. Hygroscopic growth of aerosol particles was found to cause 1.6 to 3.7 times more negative ADRE at the surface, with the smallest effect during the haze period (March-April-May) and the highest during late summer and beginning of fall (July-August-September).Peer reviewe

Vocation, Belongingness, and Balance: A Qualitative Study of Veterinary Student Well-Being

An elevated risk for suicide among veterinarians has stimulated research into the mental health of the veterinary profession, and more recently attention has turned to the veterinary student population. This qualitative study sought to explore UK veterinary students' perceptions and experiences of university life, and to consider how these may affect well-being. Semi-structured interviews were conducted with 18 students from a single UK school who were purposively selected to include perspectives from male, female, graduate-entry, standard-entry (straight from high school), and widening participation students across all 5 years of the program. Three main themes were identified: a deep-rooted vocation, navigating belongingness, and finding balance. Participants described a long-standing goal of becoming a veterinarian, with a determination reflected by often circuitous routes to veterinary school and little or no consideration of alternatives. Although some had been motivated by a love of animals, others were intrinsically interested in the scientific and problem-solving challenges of veterinary medicine. Most expressed strong feelings of empathy with animal owners. The issue of belongingness was central to participants' experiences, with accounts reflecting their efforts to negotiate a sense of belongingness both in student and professional communities. Participants also frequently expressed a degree of acceptance of poor balance between work and relaxation, with indications of a belief that this imbalance could be rectified later. This study helps highlight future avenues for research and supports initiatives aiming to nurture a sense of collegiality among veterinary students as they progress through training and into the profession

Morphological variants of silent bared-teeth displays have different social interaction outcomes in crested macaques (Macaca nigra)

Objectives: While it has been demonstrated that even subtle variation in human facial expressions can lead to significant changes in the meaning and function of expressions, relatively few studies have examined primate facial expressions using similarly objective and rigorous analysis. Construction of primate facial expression repertoires may, therefore, be oversimplified, with expressions often arbitrarily pooled and/or split into subjective pigeonholes. Our objective is to assess whether subtle variation in primate facial expressions is linked to variation in function, and hence to inform future attempts to quantify complexity of facial communication. Materials and Methods: We used Macaque Facial Action Coding System, an anatomically based and hence more objective tool, to quantify “silent bared‐teeth” (SBT) expressions produced by wild crested macaques engaging in spontaneous behavior, and utilized discriminant analysis and bootstrapping analysis to look for morphological differences between SBT produced in four different contexts, defined by the outcome of interactions: Affiliation, Copulation, Play, and Submission. Results: We found that SBT produced in these contexts could be distinguished at significantly above‐chance rates, indicating that the expressions produced in these four contexts differ morphologically. We identified the specific facial movements that were typically used in each context, and found that the variability and intensity of facial movements also varied between contexts. Discussion: These results indicate that nonhuman primate facial expressions share the human characteristic of exhibiting meaningful subtle differences. Complexity of facial communication may not be accurately represented simply by building repertoires of distinct expressions, so further work should attempt to take this subtle variability into account

Evaluation of Etiquette Strategies to Adapt Feedback In Affect-Aware Tutoring

The purpose of this research is to investigate how to mitigate user frustration and improve task performancein the context of human-computer interaction (HCI). Even though user frustration plays a role in manyaspects of HCI and studies have looked into the consequences of frustration in various fields, the ways tomitigate frustration are less deeply examined. Once the system has the ability to understand and includeuser emotions as factors in HCI, the interaction between the user and the computer system could be adaptedif the computers are able to modify its behavior with users in appropriate ways to further joint performance.Specifically, a preliminary study was conducted to explore the task performance, motivation, andconfidence implications of changing the interaction between the human and the computer via differentetiquette strategies. Participants solved a total of twenty mathematics problems under different frustrationcondition with feedback given in different styles of etiquette. Changing etiquette strategies in tutoring ledto changes in performance, motivation, and confidence. The most effective etiquette strategies changedwhen users were frustrated. This work provides the foundation for the design of adaptive intelligenttutoring system based on etiquette strategies.Copyright Human Factors and Ergonomics Society 2016. Posted with permission.</div

The analysis of facial beauty: an emerging area of research in pattern analysis

Much research presented recently supports the idea that the human perception of attractiveness is data-driven and largely irrespective of the perceiver. This suggests using pattern analysis techniques for beauty analysis. Several scientific papers on this subject are appearing in image processing, computer vision and pattern analysis contexts, or use techniques of these areas. In this paper, we will survey the recent studies on automatic analysis of facial beauty, and discuss research lines and practical application

Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema

In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011