Deterministic initialization of hidden Markov models for human action recognition

Human action recognition is often approached in terms of probabilistic models such as the hidden Markov model or other graphical models. When learning such models by way of Expectation-Maximisation algorithms, arbitrary choices must be made for their initial parameters. Often, solutions for the selection of the initial parameters are based on random functions. However, in this paper, we argue that deterministic alternatives are preferable, and propose various methods. Experiments on a video dataset prove that the deterministic initialization is capable of achieving an accuracy that is comparable to or above the average from random initializations and suffers from no deviation thanks to its deterministic nature. The methods proposed naturally extend to be used with other graphical models such as dynamic Bayesian networks and conditional random fields. © 2009 IEEE

Overview of contextual tracking approaches in information fusion

Proceedings of: Geospatial InfoFusion III. 2-3 May 2013 Baltimore, Maryland, United States.Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change over varying contexts. One example is weather data for electro-optical target trackers of which standards have evolved over decades. The operating conditions of: technology changes, sensor/target variations, and the contextual environment can inhibit performance if not included in the initial systems design. In this paper, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support target tracking: (1) domain knowledge from a user to aid the information fusion process through selection, cueing, and analysis, (2) environment-to-hardware processing for sensor management, (3) known distribution of entities for situation/threat assessment, (4) historical traffic behavior for situation awareness patterns of life (POL), and (5) road information for target tracking and identification. Appropriate characterization and representation of contextual information is needed for future high-level information fusion systems design to take advantage of the large data content available for a priori knowledge target tracking algorithm construction, implementation, and application.Publicad