Art Therapy in the Mainstream Classroom

The purpose of this project will be to provide art educators with a curricular unit plan that is based on the premise of art therapy. There will be little emphasis on the interpretation of images; the main concern will be with the idea of how the creative process can be therapeutic. The art teacher should be able to use the unit plan with a diverse range of students, from the emotionally stable to the emotionally disturbed

Effects Of Personality On Conflict Resolution In Student Teams: A Structural Equation Modeling Approach

This paper reports results of a study of the effects of five personality dimensions on conflict resolution preferences in student teams. Two hundred and sixteen students provided self-reports of personality dimensions and conflict styles using the Neo-FFI and ROCI-II scales. Simultaneous effects of five personality dimensions on five conflict resolution styles were modeled using Partial Least Squares (PLS) procedures. Results indicate that agreeableness, openness, conscientiousness, and extroversion impacted conflict resolution styles, whereas neuroticism did not. Findings are discussed along with their implications for team formation, team training, and conflict mediation

Effects Of Personality On Attitudes Toward Academic Group Work

This study investigated the effects of personality on attitudes toward academic group work among a sample of 225 business students.  Data were collected using pre-existing scales for measuring personality and attitudes toward academic group work.  Specifically, the Neo-FFI scale was used to measure the five personality dimensions of openness, agreeableness, extroversion, conscientiousness and neuroticism.  Regression analysis indicated that extroversion was the best predictor of respondents’ attitudes toward academic group work.  Individuals with high extroversion scores had positive attitudes toward academic group work.  Neuroticism, agreeableness and conscientiousness were also related to respondents’ preference for group work and discomfort with group work.  Interestingly, respondents’ level of openness had no impact on any of the work group attitude variables. &nbsp

Factors That Influence Students To Participate In Team Decision Making

This study investigated the effects of personality on participation in decision making in a sample of 225 business students. The Neo-FFI scale was used to measure the five personality dimensions of openness, agreeableness, extroversion, conscientiousness and neuroticism. Analysis indicated that personality dimensions, extroversion and conscientiousness, influenced participation. No participation influence was observed for other personality variables. Partial Least Squares modeling indicated that the extroversion and conscientiousness influences were mediated by other variables. The effect of extroversion was fully mediated by an intervening variable representing the choice to use competitive strategies for achieving success. The effect of conscientiousness was mediated by citizenship behavior as well as the choice to use competitive strategies

Synthesizing Normalized Faces from Facial Identity Features

We present a method for synthesizing a frontal, neutral-expression image of a person's face given an input face photograph. This is achieved by learning to generate facial landmarks and textures from features extracted from a facial-recognition network. Unlike previous approaches, our encoding feature vector is largely invariant to lighting, pose, and facial expression. Exploiting this invariance, we train our decoder network using only frontal, neutral-expression photographs. Since these photographs are well aligned, we can decompose them into a sparse set of landmark points and aligned texture maps. The decoder then predicts landmarks and textures independently and combines them using a differentiable image warping operation. The resulting images can be used for a number of applications, such as analyzing facial attributes, exposure and white balance adjustment, or creating a 3-D avatar

Unsupervised Training for 3D Morphable Model Regression

We present a method for training a regression network from image pixels to 3D morphable model coordinates using only unlabeled photographs. The training loss is based on features from a facial recognition network, computed on-the-fly by rendering the predicted faces with a differentiable renderer. To make training from features feasible and avoid network fooling effects, we introduce three objectives: a batch distribution loss that encourages the output distribution to match the distribution of the morphable model, a loopback loss that ensures the network can correctly reinterpret its own output, and a multi-view identity loss that compares the features of the predicted 3D face and the input photograph from multiple viewing angles. We train a regression network using these objectives, a set of unlabeled photographs, and the morphable model itself, and demonstrate state-of-the-art results.Comment: CVPR 2018 version with supplemental material (http://openaccess.thecvf.com/content_cvpr_2018/html/Genova_Unsupervised_Training_for_CVPR_2018_paper.html