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020 _a9783031502699
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024 7 _a10.1007/978-3-031-50269-9
_2doi
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_2bicssc
072 7 _aCOM016000
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072 7 _aUYQV
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082 0 4 _a006.37
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245 1 0 _aModeling Visual Aesthetics, Emotion, and Artistic Style
_h[electronic resource] /
_cedited by James Z. Wang, Reginald B. Adams, Jr.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXXXI, 396 p. 103 illus., 79 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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505 0 _aModels 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 -- ExpressionFlow: 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.
520 _aModeling 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. This book sets itself apart with its unique multidisciplinary approach, encouraging collaboration across related domains. Packed with comprehensive tutorials, theoretical reviews, novel methodologies, empirical investigations, and comparative analyses, the book offers a rich combination of knowledge and methodologies. The book's focus on cutting-edge research not only presents the latest developments in the field but also illuminates potential paths that can lead to significant advancements in computer and robotic applications.
650 0 _aComputer vision.
650 0 _aMachine learning.
650 0 _aPsychology.
650 0 _aAesthetics.
650 0 _aDigital humanities.
650 1 4 _aComputer Vision.
650 2 4 _aMachine Learning.
650 2 4 _aPsychology of Aesthetics.
650 2 4 _aDigital Humanities.
700 1 _aWang, James Z.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aAdams, Jr., Reginald B.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031502682
776 0 8 _iPrinted edition:
_z9783031502705
776 0 8 _iPrinted edition:
_z9783031502712
856 4 0 _uhttps://doi.org/10.1007/978-3-031-50269-9
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912 _aZDB-2-SXCS
942 _cSPRINGER
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