A new method to enhance the performance of multi radar tracking systems is presented in this paper. In parallel to an IMM model type tracker a second tracker estimates track heading and speed based upon differential measurements from multiple sensors. A differential measurement contains the differences between two subsequent measurements from one sensor. This new method accepts information from...

This paper finds upper bounds for the generalization error of three tracking algorithms when confronted with a worst case adversary. A system identification model is used where both the target and tracking network are single layer threshold networks, with the target weights changing slowly (the drift problem). Previous work considered random unbiased drifting adversaries. This paper focuses on ...

Visual tracking is considered to be one of the most important challenges in computer vision with numerous applications such as object recognition and detection.Inthe present paper, four tracking techniques will be introduced circulant structure with kernels (CSK), Kernelized correlation filters (KCF), Adaptive color attributes (ACT), and distractor – awareness tracker (DAT) for the visual objec...

Following an expected increase of the LHC luminosity beyond its design value of 1034 cm−2s−1 the CMS collaboration is planning for a series of upgrades on the experimental apparatus. In particular the silicon tracker should undergo two major upgrades to cope with the increased luminosity of the collider. The first intervention (Phase I) concerns a replacement of the pixel system, the rest of th...

Multistatic active sonar systems are being developed for the mission of tracking enemy submarines in harsh underwater environments. This paper will focus on a revolutionary new method with which to track a target. A fuzzy logic based tracker has been developed which performs remarkably better than a Kalman filter tracker. This is accomplished through the use of additional, non-kinematic informa...

This paper analyzes the behavior of a variety of tracking algorithms for single-layer threshold networks in the presence of random drift. We use a system identification model to model a target network where weights slowly change and a tracking network. Tracking algorithms are divided into conservative and nonconservative algorithms. For a random drift rate of , we find upper bounds for the gene...

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of...

Object tracking is widely used in many applications such as intelligent surveillance, scene understanding, and behavior analysis. Graph-based semisupervised learning has been introduced to deal with specific tracking problems. However, existing algorithms following this idea solely focus on the pairwise relationship between samples and hence could decrease the classification accuracy for unlabe...

We describe a facial feature tracker based on the combined range and amplitude data provided by a 3D time-of-flight camera. We use this tracker to implement a head mouse, an alternative input device for people who have limited use of their hands. The facial feature tracker is based on geometric features that are related to the intrinsic dimensionality of multidimensional signals. We show how th...

This thesis presents a framework for tracking head movements and capturing the movements of the mouth and both the eyebrows in real-time. We present a head tracker which is a combination of a optical flow and a template based tracker. The estimation of the optical flow head tracker is used as starting point for the template tracker which fine-tunes the head estimation. This approach together wi...