Multimodal Collaborative Perception for Unmanned Systems (Advances in Computer Vision and Pattern Recognition)

This book focuses on multimodal collaborative perception-a cornerstone for unmanned systems.As connected vehicles, autonomous driving, and UAV-based monitoring continue to evolve, the ability to integrate diverse sensor data into reliable, real-time situational awareness becomes crucial.This book speaks directly to researchers, graduate students, and professionals who want to understand both the technical foundations and practical applications of collaborative perception. Structured to bridge theory and practice, the book offers a comprehensive exploration that begins with sensor principles and preprocessing, advances through state estimation, collaborative object detection, tracking, and localization, and culminates in real-world applications in autonomous driving and UAV monitoring.Readers will discover how classical models such as Kalman filtering merge with cutting-edge deep learning techniques, how multimodal data fusion enhances perception under complex conditions, and how digita