The expectation maximisation algorithm (EM) was introduced by Dempster, Laird and Rubin in 1977 [DLR77]. The basic of expextation maximisation is maximum likelihood estimation (MLE). In modern sensor data fusion expectation maximisation becomes a substantial part in several applications, e.g. multi target tracking with probabilistic multi hypothesis tracking (PMHT), target extraction within pro...

Object tracking is a challenging task in many computer vision applications due to occlusion, scale variation and background clutter, etc. In this paper, we propose a tracking algorithm by combining discriminative global and generative multi-scale local models. In the global model, we teach a classifier with sparse discriminative features to separate the target object from the background based o...

SACHIN B. JADHAV Department of E & TC, Shivaji University, Bharati Vidyapeeth’s College of Engineering, Kolhapur, India, * [email protected] ABSTRACT In this paper, we consider multi-object target tracking using video reference datasets. Our objective is detection of the target using a novel adaboost and Gentle Boost method in order to track the subjects from reference data sets. Mult...

We consider nonlinear filtering applications to target tracking based on a vector of multi-scaled models where some of the processes are rapidly mean reverting to their local equilibria. We focus attention on target tracking problems because multiple scaled models with fast mean-reversion (FMR) are a simple way to model latency in the response of tracking systems. The main results of this paper...

Two-tier network structure is usually used to lighten the energy consumption in Wireless Multimedia Sensor Networks (WMSNs) for large scale surveillance application. Previous methods for target tracking in two-tier WMSNs mostly focused on reducing energy cost to prolong lifetime of the networks without considering the effect of visual target tracking. This paper presents a collaborative multi-t...