This paper addresses the problem of tracking a dim moving point target in a sequence of IR images. The proposed tracking system, based on the track-before-detect (TBD) approach, is designed to track and detect dim maneuvering targets from an image sequence under low SNR conditions; a dynamic programming algorithm (DPA) is used to process the frames in the sequence. This paper deals with the pra...

Representation and reasoning about time-dependent information is an active and important research area in Artificial Intelligence and in Computer Science. Vilain and Kautz’s point algebra (see [VK86]) is one of the most influential models used for representing and reasoning with qualitative time information, because the reasoning tasks are solvable in polynomial time in that model, contrary to ...

In this article, we propose a new extension to a Dynamic Programming Algorithm (DPA) approach for Track-beforeDetect challenges. This extension enables the DPA to process time-delayed sensor data directly. Such delay might appear because of delays in communication networks. The extended DPA is identical to the recursive standard DPA in case of all sensor data appear in the timely correct order....

We describe a video tracking application using the dual-tree Polar Matching Algorithm. We develop the dynamical and observation models in a probabilistic setting and study the empirical probability distribution of the Polar Matching output. We model the visible and occluded target statistics using Beta distributions. This is incorporated into a Track-Before-Detect (TBD) solution for the overall...

An algorithm has been developed for the detection of point targets in uncluttered background based on a Bayesian track before detect method. The algorithm has an application in the detection of sea skimming antiship missiles at maximum range, when the missile appears over the horizon. Because of the long range, angular motion of the target will be insignificant, and target motion cannot be used...

The Histogram Probabilistic Multi-Hypothesis Tracker (H-PMHT) algorithm is a parametric track-before-detect method. It locates targets in imagery by fitting a mixture of probability densities. In recent work, an unknown target shape was accommodated through the use of a Wishart prior on the measurement probability density, this version of the algorithm is referred to as H-PMHT-RM. This paper ap...

While there is no consensus about the history of time since the beginning, in this paper I will discuss some possibilities. We have a pretty clear picture of cosmic history from the electroweak phase transition through the time of recombination, a period which includes the QCD phase transition and big bang nucleosynthesis. This paper includes a quantitative discussion of the age of the universe...

Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially PMHT is based on expectation-maximization for handling with association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodo...

In this paper, we are studied the problem of data associating in track-before detect (TBD) multiple radar system. The influence of trajectory parameters accuracy (errors) on the quality of work of TBD multiradar system is estimated. We suppose the Hough space discretization to be two times larger than max measure error of target co-ordinate.

S INCE ABOUT 1980 THERE HAS BEEN UNPRECEDENTED global economic integration. Globalization has happened before, but not like this. Economic integration occurs through trade, migration, and capital flows. Figure 1.1 tracks these flows. World trade is measured relative to world income. Capital flows are proxied by the stock of foreign capital in developing countries relative to their GDP. Migratio...