James Z. Wang & Reginald B. Adams, Jr. 
Modeling Visual Aesthetics, Emotion, and Artistic Style [PDF ebook] 

Models of Human Emotion and Artificial Emotional Intelligence.- A Concise Introduction to Machine Learning.- Facing a Perceptual Crossroads: Mixed Messages and Shared Meanings in Social Visual Perception.- Social Vision of the Body In Motion: Interactions Between the Perceiver and the Perceived.- Visual Perception of Threat: Structure, Dynamics, and Individual Differences.- From Pixels to Power: Critical Feminist Questions for the Ethics of Computer Vision.- High-Speed Joint Learning of Action Units and Facial Expressions.- Expression Flow: A Microexpression Descriptor for Efficient Recognition.- Emotion in the Neutral Face: Applications for Computer Vision and Aesthetics.- Multi-stream Temporal Networks for Emotion Recognition in Children and In the Wild.- The Formal Language of Photography: A Primer.- Breathing With Robots: Notating Performer Strategy, Alongside Choreographer Intent and Audience Observation, In Breath-driven Robotic Dance Performance.- Humanist-in-the-Loop: Machine Learning and the Analysis of Style in the Visual Arts.- The Inter-relationship between Photographic Aesthetics and Technical Quality.- Image Restoration for Beautification.- Image Affect Modeling: An Industrial Perspective.- Emotional Expression as a Means of Communicating Virtual Human Personalities.- Modeling Emotion Perception from Body Movements for Human-Machine Interactions using Laban Movement Analysis.- Demographic Differences and Biases in Affect Evoked by Visual Features.- Deep Network-based Computational Transfer of Artistic Style in Art Analysis.- Balance of Unity and Variety in Fine Art Paintings: A Computational Study.

James Z. Wang is a Distinguished Professor of the College of Information Sciences and Technology at The Pennsylvania State University. He received a bachelor’s degree in mathematics
summa cum laude from the University of Minnesota (1994), and an M.S. degree in mathematics (1997), an M.S. degree in computer science (1997), and a Ph.D. in medical information sciences (2000), all from Stanford University. His research interests include affective computing, image analysis, image modeling, image retrieval, and their applications. He was a visiting professor at the Robotics Institute at Carnegie Mellon University (2007-2008), a lead special section guest editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence (2008), and a program manager at the Office of the Director of the National Science Foundation (2011-2012).
Reginald B. Adams, Jr. is a Professor of Psychology at The Pennsylvania State University. He received his Ph.D. in social psychology from Dartmouth College in 2002. Reg is interested in how we extract social and emotional meaning from nonverbal cues, particularly via the face. His work addresses how multiple social messages (e.g., emotion, gender, race, age, etc.) combine across multiple modalities and interact to form the unified representations that guide our impressions of and responses to others. Although his questions are social psychological in origin, his research draws upon vision cognition and affective neuroscience to address social perception at the functional and neuroanatomical levels. With his colleagues, Reg helped establish and champion the subfield of Social Vision by publishing an edited volume titled The Science of Social Vision (Adams, Ambady, Nakayama, & Shimojo, 2010, Oxford University Press).