Artificial Intelligence for Human Computer Interaction: A Modern Approach / edited by Yang Li, Otmar Hilliges.

Format:

Book

Contributor:

Li, Yang, Editor.

Hilliges, Otmar., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Human-computer interaction series 2524-4477

Human-Computer Interaction Series, 2524-4477

Language:

English

Subjects (All):

User interfaces (Computer systems).

Human-computer interaction.

Artificial intelligence.

User Interfaces and Human Computer Interaction.

Artificial Intelligence.

Local Subjects:

User Interfaces and Human Computer Interaction.

Artificial Intelligence.

Physical Description:

1 online resource (XX, 595 pages) : 228 illustrations, 216 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.

Contents:

Introduction

Part 1: Modeling

Human performance modeling with deep learning

Optimal control to support high-level user goals in human-computer interaction.-Modeling UI tappability using deep learning and crowdsourcing

Part 2: Input

Eye gaze estimation and its applications

AI-driven intelligent text correction techniques for mobile text entry

Deep touch: Sensing press gestures from touch image sequences

Deep learning-based hand posture recognition for pen interaction enhancement

Part 3: Data and tools

An early Rico retrospective: Three years of uses for a mobile app dataset

Visual intelligence through human interaction

ML tools for the web: A way for rapid prototyping and HCI research

Interactive reinforcement learning for autonomous behavior design

Part 4: Specific domains

Sketch-based creativity support tools using deep learning

Generative link: Data-driven computational models for digital ink

Bridging natural language and graphical user interfaces

Demonstration + natural language: Multimodal interfaces for GUI-based interactive task learning agents

Human-centred AI for medical imaging

3D spatial sound individualization with perceptual feedback.

Other Format:

Printed edition:

ISBN:

978-3-030-82681-9

9783030826819

Access Restriction:

Restricted for use by site license.