Uploaded June 2024 | Updated September 2026, 4 hours ago
Developed by students in the Spring 2024 AR/VR Capstone Class, at UW CSE.
Cat-astrophe is an immersive VR language learning game where the player is in a foreign town, has lost their cat, and must interact with locals to gain hints and find it. Player interactions with characters include scored, AI-powered pronunciation and reading/translation tasks in Spanish, and players can explore the town to expand their Spanish vocabulary of common objects.
The AR/VR Capstone Class, at UW CSE (University of Washington's Allen School of Computer Science & Engineering) is an intensive 10-week class introducing students to AR/VR, Unity, and to developing software apps as a team. This year every team incorporated generative AI into their projects through asset creation, conversational agents, and state management systems.
Capstone Class: https://courses.cs.washington.edu/courses/cse481v/24sp/
Reality Lab Lectures: tinyurl.com/RealityLabLectures
© UW Reality Lab, 2024
http://realitylab.uw.edu
Developed by students in the Spring 2024 AR/VR Capstone Class, at UW CSE.
Cat-astrophe is an immersive VR language learning game where the player is in a foreign town, has lost their cat, and must interact with locals to gain hints and find it. Player interactions with characters include scored, AI-powered pronunciation and reading/translation tasks in Spanish, and players can explore the town to expand their Spanish vocabulary of common objects.
The AR/VR Capstone Class, at UW CSE (University of Washington's Allen School of Computer Science & Engineering) is an intensive 10-week class introducing students to AR/VR, Unity, and to developing software apps as a team. This year every team incorporated generative AI into their projects through asset creation, conversational agents, and state management systems.
Capstone Class: https://courses.cs.washington.edu/courses/cse481v/24sp/
Reality Lab Lectures: tinyurl.com/RealityLabLectures
© UW Reality Lab, 2024
http://realitylab.uw.edu
![Reality Lab Lectures: Gordon Wetzstein - Computational Near-eye Displays [VR180]](https://i.ytimg.com/vi/5CwQ5O64s2Q/mqdefault.jpg "Reality Lab Lectures: Gordon Wetzstein - Computational Near-eye Displays [VR180]
[Filmed in VR180. For the 3D experience, please view with Cardboard, Daydream or PSVR]
The Reality Lab Lectures - Friday, June 8, 2018
Talk Title: Computational Near-Eye Displays: Engineering the Interface Between Our Visual System and the Digital World
Speaker: Gordon Wetzstein (Asst. Professor of Electrical Engineering at Stanford University, leader of the Stanford Computational Imaging Lab)
Recording Details: This recording was made with a Z CAM K1 Pro 3D camera.
Close Captions: This talk was also recorded with traditional 2D cameras with close captioning, available here: https://youtu.be/BXnDXAQpmWg
Talk Abstract: Immersive visual and experiential computing systems, i.e. virtual and augmented reality (VR/AR), are entering the consumer market and have the potential to profoundly impact our society. Applications of these systems range from communication, entertainment, education, collaborative work, simulation and training to telesurgery, phobia treatment, and basic vision research. In every immersive experience, the primary interface between the user and the digital world is the near-eye display. Thus, developing near-eye display systems that provide a high-quality user experience is of the utmost importance. Many characteristics of near-eye displays that define the quality of an experience, such as resolution, refresh rate, contrast, and field of view, have been significantly improved over the last years. However, a significant source of visual discomfort prevails: the vergence-accommodation conflict (VAC). Further, natural focus cues are not supported by any existing near-eye display. In this talk, we discuss frontiers of engineering next-generation opto-computational near-eye display systems to increase visual comfort and provide realistic and effective visual experiences.
Event held on the UW-Seattle Campus
© UW Reality Lab, 2018
http://realitylab.uw.edu")
