Computer Vision
Computer Vision
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Professor: Douglas Rosman
Assistant Professor, Art & Technology / Sound Practices
Email: drosman@saic.edu, https://sites.saic.edu/mfa2019/artist/douglas-rosman/
Wednesdays 9 am - 3 pm
Department: Art & Technology / Sound Practices
Department: Art & Technology / Sound Practices
Area of Study: Art & Sicence, AI, Deep Learning, Surveilance, Face & Body Recognition, Machine Learning, P5js & TouchDesigner.
Area of Study: Art & Sicence, AI, Deep Learning, Surveilance, Face & Body Recognition, Machine Learning, P5js & TouchDesigner.
Location: In person, Maclean 401
Location: In person, Maclean 401
Teaching Assistant: Rose Ansari, MFA ransar@saic.edu
Description
Computer vision allows machines to see and understand their environment. This course will equip students with the practical skills and critical theory needed to both employ and critically engage these techniques. Real-time body tracking, facial recognition and gesture analysis using RGB+D and LiDAR sensors, artificial intelligence and machine learning will be emphasized. Students will explore and critique contemporary applications ranging from automated mass surveillance to interactive installations. A final project will build on in-class workshops, technical exercises, critical readings and discussions.
About the Professor
About the Professor
Education: BA, 2014, University of California, San Diego; MFA 2019, School of the Art Institute of Chicago. Exhibitions: Max Ernst Museum, Brühl; Ming Contemporary Art Museum, Shanghai; Ars Electronica, Linz; iMAL Art Center for Digital Cultures & Technology, Brussels; Kunstuniversität, Linz; Teatros del Canal; Madrid; Elastic Arts, Chicago; LITHIUM Gallery, Chicago; The Wrong Biennale. Bibliography: Performing Identities, Tina Sauerlaender.
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