A new method for multiple model particle filtering for Markovian switching systems is
presented. This new method is a combination of the interacting multiple model (IMM) filter …

Pedestrian tracking and detection have become critical aspects of advanced driver
assistance systems (ADASs), due to their academic and commercial potential. Their …

We address the problem of jointly tracking and classifying several targets within a sensor
network where false detections are present. In order to meet the requirements inherent to …

The use of kinematic measurements for target classification has been explored recently by
several authors. This paper formulates the general framework for optimal Bayesian …

Many problems involve joint decision and estimation, where qualities of decision and
estimation affect each other. This paper proposes an integrated approach based on a new …

Target detection and tracking represent two fundamental steps in automatic video-based
surveillance systems where the goal is to provide intelligent recognition capabilities by …

The paper develops an approach to joint tracking and classification based on belief
functions as understood in the transferable belief model (TBM). The TBM model is identical …

This paper considers the problem of joint maneuvering target tracking and classification.
Based on recently proposed Monte Carlo techniques, a multiple model (MM) particle filter …

The subject of this thesis is belief function theory and its application in different contexts.
Belief function theory can be interpreted as a generalization of Bayesian probability theory …

To account for joint detection, tracking, and classification (JDTC) of multiple targets from a
sequence of noisy and cluttered observation sets, this paper introduces a recursive …