Description
Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links.This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing.- Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios- Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources- Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data
Table of Contents
1. Multimodal open-domain conversations with robotic platforms2. Audio-motor integration for robot audition3. Audio source separation into the wild4. Designing audio-visual tools to support multisensory disabilities5. Audio-visual learning for body-worn cameras6. Activity recognition from visual lifelogs: State of the art and future challenges7. Lifelog retrieval for memory stimulation of people with memory impairment8. Integrating signals for reasoning about visitors' behavior in cultural heritage9. Wearable systems for improving tourist experience10. Recognizing social relationships from an egocentric vision perspective11. Complex conversational scene analysis using wearable sensors12. Detecting conversational groups in images using clustering games13. We are less free than how we think: Regular patterns in nonverbal communication14. Crowd behavior analysis from fixed and moving cameras15. Towards multi-modality invariance: A study in visual representation16. Sentiment concept embedding for visual affect recognition17. Video-based emotion recognition in the wild18. Real-world automatic continuous affect recognition from audiovisual signals19. Affective facial computing: Generalizability across domains20. Automatic recognition of self-reported and perceived emotions
