정보대학에서 Multi Object (Target) Estimation and Tracking 관련 세미나를 진행합니다.

주제: Estimation for Finite-set-valued State Space Models
일시: 10/30(화) 17:00
장소: 자연계 우정정보관 601호
연사: Prof. Ba-Ngu Vo (Dept. of Electrical and Computer Engineering at Curtin University, Australia)

Abstract: In a finite-set-valued State Space Model (SSM) or Hidden Markov Model (HMM), the hidden state is a finite set. Such an SSM describes a multi-object system, a system in which the number of objects and their states are unknown and vary randomly with time. Multi-object systems arise in many research disciplines including surveillance, computer vision, robotics, biomedical research and machine learning. Indeed, most systems in nature can be regarded as multi-object systems. The last decade has witnessed exciting developments with the introduction of stochastic geometry to finite-set-valued SSM. This talk presents recent developments in smoothing and filtering for finite-set-valued SSMs with applications in multiple object tracking, especially large-scale problems.

Biography: Ba-Ngu Vo received his Bachelor degrees in Pure Mathematics and Electrical Engineering with first class honours in 1994, and PhD in 1997. Currently he is Professor and Chair of Signals and Systems in the Department of Electrical and Computer Engineering at Curtin University. Vo is a recipient of the Australian Research Council’s inaugural Future Fellowship and the 2010 Eureka Prize for Outstanding Science in support of Defense or National Security. He is an associate editor of the IEEE Transaction on Aerospace and Electronic System. Vo is best known as a pioneer in the stochastic geometric approach to multi-object system. His research interests are signal processing and stochastic geometry with emphasis on target tracking, space situational awareness, and computer vision.