Multimodal Behavior Analysis in the Wild
Advances and Challenges
by Xavier Alameda-Pineda, Elisa Ricci, Nicu Sebe
1st Edition
Publisher: Academic Press
Book Details
| Print ISBN | 9780128146019 |
| eText ISBN | 9780128146026 |
| Publisher | Academic Press |
| Publishing Year | 2018 |
| Edition | 1st Edition |
| Language | English |
| Pages | 498 |
Multimodal Behavior Analysis in the Wild: Advances and Challenges, 1st Edition, examines methodologies and applications for extracting human behavioral cues from multimodal data in unconstrained environments.
The volume concentrates primarily on audio and video modalities while also incorporating emerging inputs such as accelerometer and proximity data. Coverage spans behavioral tasks across low, middle, and high levels of complexity, from low-level sensory processing to conversational dynamics and high-level affect estimation.
Designed for researchers and graduate students in computer vision, machine learning, pattern recognition, and social signal processing, the book addresses the strengths and limitations of deploying behavioral analysis technologies in everyday settings.
Table of Contents
Chapter 1: Multimodal open-domain conversations with robotic platforms
Chapter 2: Audio-motor integration for robot audition
Chapter 3: Audio source separation into the wild
Chapter 4: Designing audio-visual tools to support multisensory disabilities
Chapter 5: Audio-visual learning for body-worn cameras
Chapter 6: Activity recognition from visual lifelogs: State of the art and future challenges
Chapter 7: Lifelog retrieval for memory stimulation of people with memory impairment
Chapter 8: Integrating signals for reasoning about visitors’ behavior in cultural heritage
Chapter 9: Wearable systems for improving tourist experience
Chapter 10: Recognizing social relationships from an egocentric vision perspective
Chapter 11: Complex conversational scene analysis using wearable sensors
Chapter 12: Detecting conversational groups in images using clustering games
Chapter 13: We are less free than how we think: Regular patterns in nonverbal communication
Chapter 14: Crowd behavior analysis from fixed and moving cameras
Chapter 15: Towards multi-modality invariance: A study in visual representation
Chapter 16: Sentiment concept embedding for visual affect recognition
Chapter 17: Video-based emotion recognition in the wild
Chapter 18: Real-world automatic continuous affect recognition from audiovisual signals
Chapter 19: Affective facial computing: Generalizability across domains
Chapter 20: Automatic recognition of self-reported and perceived emotions
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