Multi-target tracking problems are traditionally tackled in two different ways. One way is to first group detections into candidate tracklets and then perform scoring and association of these tracklets [5, 6], this can be done in either an online/streaming fashion or an offline/batch fashion and it allows tracklets to be scored with richer trajectory and appearance models. Another approach is t...

In this paper we propose a new method to detect and track multiple moving targets on image sequences recorded by Unmanned Aerial Vehicles (UAVs). Our approach focuses on challenging urban scenarios, where several object are simultaneously moving in various directions, and we must expect frequent occlusions caused by other moving vehicles or static scene objects such as buildings and bridges. In...

We consider the problem of tracking multiple, partially observed targets using multiple sensors arranged in a given configuration. We model the problem as a special case of a (finite horizon) DECPOMDP. We present a quadratic program whose globally optimal solution yields an optimal tracking joint policy, one that maximizes the expected targets detected over the given horizon. However, a globall...

Abstract In this paper, we present a multi-sensor cooperation paradigm between an omnidirectional vision system and a panoramic range finder system, using to localize dynamically a mobile robot. These two sensors provide some complementary data which enable us to build a robust sensorial model which integrates an important number of significant primitives. Based on this model we treat the probl...

Target detection and tracking is an important problem in the automatic surveillance system. This paper proposes a Combined Gaussian Hidden Markov Model based Kalman Filter (CGHMM-KF) scheme for tracking people in multiple camera sensor network for monitoring and tracking of target (person/vehicle) in secured area. To detect the target under different illumination conditions, HMM with Mixture of...

The objective of this thesis is to develop a new framework for Multi-Target Tracking (MTT) algorithms that are distinguished by the use of statistical machine learning techniques. MTT is a crucial problem for many important practical applications such as military surveillance. Despite being a well-studied research problem, MTT remains challenging, mostly because of the challenges of computation...

This paper considers the problem of designing a realtime surveillance system, equipped with a single camera on a pan/tilt platform, to track multiple moving targets within the camera’s field of regard. The objective is to maintain motion trajectory information of as many of these targets as possible, and for as long as possible. Because the camera can only capture a fraction of the field of reg...

The problem of limited sensor resolution, although usually ignored in target tracking, occurs in multi-target scenarios whenever the target distance falls below the size of the sensor resolution cell. Typical examples are the surveillance of aircraft in formation, and convoy tracking for ground surveillance. Ignoring the limited sensor resolution in a tracking system may lead to degraded tracki...

This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking problems and for estimating the number of components in mixture models. Traditional solutions for the single target tracking problem becomes infeasible when the number of targets grows. Furthermore, when the number of t...

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including ...