Our work concerns multitarget tracking (MTT) for SDI using optical processing. Our 3 layer system: detection, track initiation, and tracking was detailed in prior reports. Our present work involves a modified optical correlator and a new algorithm for detection, Hough transform extensions for track initiation, and new MTT data and algorithms. We now provide an overview of this work with details given in associated chapters.

Our work has emphasized analog optical processing for three levels of multitarget tracking: target detection, track initiation and target tracking. New algorithms and new optical processing architectures have resulted and initial quantitative results have been obtained for each phase of the work. A new acousto-optic implementation of our sub-pixel target detection algorithm was devised and tested. This involved a new algorithm and architecture that achieves image registration, interpolation and subtraction. This technique is thus suitable for general image registration applications also. A 2-D Hough transform optical processors is used for track initiation. It allows accumulation of target measurements until sufficient confidence has been established that a target track exists. It provides position and velocity estimates for each target and predictions of the next vector location of each target. A new threshold Hough transform provides improved performance and reduced false alarms in noise. Very impressive results from many multiple targets were obtained. This work is also suitable for general object feature extraction and product inspection applications. We devised a completely new realization of the Joint Probabilistic Data Association Algorithm for multitarget tracking and a most attractive new acousto-optic architecture to achieve this. This also has more general use in hypothesis testing. Finally, a new analogy neural net algorithm and architecture was formulated, an optical processor to implement it was described and initial simulations of it were obtained. (fr).

Annotation This book constitutes the refereed proceedings of the 11th International Conference on Neural Information Processing, ICONIP 2004, held in Calcutta, India in November 2004. The 186 revised papers presented together with 24 invited contributions were carefully reviewed and selected from 470 submissions. The papers are organized in topical sections on computational neuroscience, complex-valued neural networks, self-organizing maps, evolutionary computation, control systems, cognitive science, adaptive intelligent systems, biometrics, brain-like computing, learning algorithms, novel neural architectures, image processing, pattern recognition, neuroinformatics, fuzzy systems, neuro-fuzzy systems, hybrid systems, feature analysis, independent component analysis, ant colony, neural network hardware, robotics, signal processing, support vector machine, time series prediction, and bioinformatics.

- The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring - Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications - Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware This book is the definitive reference in multi-camera networks. It gives clear guidance on the conceptual and implementation issues involved in the design and operation of multi-camera networks, as well as presenting the state-of-the-art in hardware, algorithms and system development. The book is broad in scope, covering smart camera architectures, embedded processing, sensor fusion and middleware, calibration and topology, network-based detection and tracking, and applications in distributed and collaborative methods in camera networks. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal and video processing, computer vision, and sensor networks. Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University. His research is on multi-camera networks for smart environments with application to smart homes, assisted living and well being, meeting rooms, and avatar-based communication and social interactions. He is Editor-in-Chief of Journal of Ambient Intelligence and Smart Environments, and was general chair of ACM/IEEE ICDSC 2008. Andrea Cavallaro is Reader (Associate Professor) at Queen Mary, University of London (QMUL). His research is on target tracking and audiovisual content analysis for advanced surveillance and multi-sensor systems. He serves as Associate Editor of the IEEE Signal Processing Magazine and the IEEE Trans. on Multimedia, and has been general chair of IEEE AVSS 2007, ACM/IEEE ICDSC 2009 and BMVC 2009. - The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring - Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications - Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware