Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Stanford University

Using Data for Increased Realism with Haptic Modeling and Devices

Stanford University via YouTube

Overview

Learn about cutting-edge haptic technology and data-driven approaches to creating realistic touch sensations in this Stanford seminar. Explore the process of haptography, including recording textures with specialized devices and synthesizing new haptic outputs. Discover how preference-driven modeling and machine learning techniques are revolutionizing haptic model tuning, surpassing traditional hand-tuned methods. Examine the development of encountered-type haptic devices and their advantages over conventional rendering methods. Delve into the fascinating world of data-driven social touch, investigating emotion accuracy in touch communication and the real-time transmission of tactile sensations. Gain insights into ongoing research on the relationship between touch speed and emotional conveyance in this comprehensive 56-minute presentation on advanced haptic modeling and devices.

Syllabus

Introduction.
HAPTOGRAPHY.
HAPTIC RECORDING DEVICE.
HAPTIC TEXTURE RECORDING PROCEDURE.
RECORDED DATA.
SOUND MODELING.
SYNTHESIZING A NEW SOUND OUTPUT.
OLD WAY: HAND TUNING MODELS.
NEW WAY: PREFERENCE-DRIVEN TUNING.
HAPTIC MODELS: FRICTION AND TEXTURE.
TEXTURE GENERATIVE MODEL.
PREFERENCE-DRIVEN MODELING FRAMEWORK.
TUNING TEXTURE MODELS.
REALISM OF MODELS.
ENCOUNTERED-TYPE HAPTIC DEVICE.
COMPARING TO TRADITIONAL RENDERING METHODS.
RESULTS: REALISM.
DATA-DRIVEN SOCIAL TOUCH.
EMOTION ACCURACY.
REAL-TIME TRANSMISSION OF TOUCH.
STUDYING EFFECT OF SPEED ON EMOTION.

Taught by

Stanford Online

Reviews

Start your review of Using Data for Increased Realism with Haptic Modeling and Devices

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.