Modeling Visual Aesthetics, Emotion by James Z. Wang (.PDF)+
File Size: 42.7 MB
Modeling Visual Aesthetics, Emotion, and Artistic Style by James Z. Wang, Reginald B. Adams, Jr.
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Overview: Modeling Visual Aesthetics, Emotion, and Artistic Style offers a comprehensive exploration of the increasingly significant topic of the complex interplay between human perception and digital technology. It embodies the cumulative knowledge and efforts of a wide array of active researchers and practitioners from diverse fields including Computer Vision, affective computing, robotics, psychology, data mining, Machine Learning, art history, and movement analysis. This volume seeks to address the profound and challenging research questions related to the computational modeling and analysis of visual aesthetics, emotions, and artistic style, vital components of the human experience that are increasingly relevant in our digitally connected world.
The book’s vast scope encompasses a broad range of topics. The initial chapters lay a strong foundation with background knowledge on emotion models and Machine Learning, which then transitions into exploring social visual perception in humans and its technological applications. Readers will uncover the psychological and neurological foundations of social and emotional perception from faces and bodies. Subsequent sections broaden this understanding to include technology’s role in detecting discrete and subtle emotional expressions, examining facial neutrality, and including research contexts that involve children as well as adults. Furthermore, the book illuminates the dynamic intersection of art and technology, the language of photography, the relationship between breath-driven robotic performances and human dance, and the application of Machine Learning in analyzing artistic styles.
Genre: Non-Fiction > Tech & Devices
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