From front-end sensors to systems and environmental issues, this practical resource guides you through the many facets of multimodal surveillance. The book examines thermal, vibration, video, and audio sensors in a broad context of civilian and military applications. This cutting-edge volume provides an in-depth treatment of data fusion algorithms that takes you to the core of multimodal surveillance, biometrics, and sentient computing. The book discusses such people and activity topics as tracking people and vehicles and identifying individuals by their speech. Systems designers benefit from discussions on 3-D scene and automatic modeling, high-end sensors for long-range tracking or high-fidelity, and low-cost sensor solutions. Developers gain new insight into architectures, frameworks, workbenches, real-time performance, and systems evaluation. Bringing together the work of leading international experts, this book is your authoritative reference on multimodal applications, methodologies, and systems implementation.
Table Of Contents
IntroductionMultimodal Sensing, Data Fusion, and Surveillance Part I: Multimodal Sensors and Sensing Approaches; Multimodal Human Signatures for Personnel Detection.; Human Signatures in Urban Environments Using Multimodal Unattended Ground Sensors.; Multimodal Image Fusion Systems.; Multimodal Integration for Human Detection and Hearing at a Distance.; Sensor and Data System, Audio-Assisted Cameras, and Acoustic Doppler Sensors.; Part II: Multimodal Integration Algorithms; Automatic Audio-Visual Speech Recognition.; Multimodal Tracking for Smart Videoconferencing and Video Surveillance.; Combination of Ear and Face Images in Appearance-Based Biometrics.; Multimodal Biometrics of Face and Palm Print.; Multisensory and Multimodal Fusion for Sentient Computing.; Part III: Multimodal Systems; EC-ASSIST: An End-to-End Electronic Chronicling System for the ASSIST Program.; Systems Issues in Multimodal Surveillance.; A Multimodal Workbench for Automatic Surveillance.; Automatic 3D Modeling of Cities with Multimodal Air and Ground Sensors.; Multimodal Biometric Systems: Applications and Usage Scenarios.; A Framework for Multimodal Sensor Stream Analysis, Transformation, and Querying. ;
Thomas Huang is the William L. Everitt Distinguished Professor of the Department of Electrical and Computer Engineering and of the Coordinated Science Lab at the University of Illinois at Champaign-Urbana. A frequent keynote speaker at professional and academic conferences, he has garnered many professional honors including the Honda Lifetime Achievement Award, IEEE Third Millennium Medal, and the IEEE Jack S. Kilby Signal Processing Medal. He holds an M.S. and Sc.D. in electrical engineering from M.I.T.
Zhigang Zhu is an associate professor in the Computer Science Department, City College of New York. An associate editor of Machine Vision and Applications Journal, he has been involved in organizing such meetings as the IEEE Virtual Reality Conference, the International Workshop on Digital and Computational Video, and the IEEE International Workshop on Image and Video Registration. He received his M.E. and Ph.D. in computer science from Tsinghua University, Beijing.