Technical University of Munich

@phdthesis{klupsch_objektorientierte_2000,
 author = {M Klupsch},
 title = {Objektorientierte Daten- und Zeitmodelle für die Echtzeit-Bildfolgenauswertung},
 school = {Fakultät für Informatik, Technische Universität München},
 year = {2000},
 abstract = {This work describes new concepts for the object-oriented modeling
	and representation of time-varying image and sensor data sequences
	as well as the functions which process these data sequences. Different
	frameworks for developing sensor data modules from function and data
	objects are presented. These allow to develop, configure and control
	these modules easily and to integrate them into complex real-time
	program systems transparently as logical sensors. The aim of this
	work is to provide a software system which supports the design and
	implementation process of efficient and scalable program components
	and applications for real-time processing of image sequences and
	distributed sensor data analysis on standard computer systems. One
	of the fundamentals of this work is a consistent, explicit modeling
	of time. This concerns the sensor based data capturing and modeling
	of the outer process as well as the description of the data processing
	system itself. The first aspect allows to relate the data to the
	course of events in the real world and to model the dynamic aspects
	of the scene, the latter provides mechanisms for analysing the performance
	of the data processing methods. Data sequences are modelled as autonomous
	objects ({'Sequence')} collecting the individual measurements of
	a specific scene state like images or other sensor data, and the
	features derived from these. In addition, they represent general
	properties and methods, which are common for all kinds of data sequences,
	such as data initialization, access to current and old values, access
	to their temporal properties, and methods for updating the data sequence
	or interpolating values. Sensors and operators are modelled as {'Functor'}
	objects, which on an abstract level provide the functionality for
	continuously capturing, transforming, or analysing the dynamic data
	sequences. They encapsulate concrete sensor integrations and operator
	sequences including their static parameters. In addition, they represent
	general, application independent operator properties, e.g., connections
	to the input and output data sequences, attributes and methods for
	analysing the time consumption, or a general interface for the cyclic
	operator execution. With the help of these Sequence and Functor objects
	the data flow representation of a sensor data module is easy to implement
	without the need for an explicit program control specificaton. Instead,
	the program components are locally executed by new input data or
	by access to the output data. That behavior can be modified according
	to topical requirements. It can be controlled by software agents.
	So, it is easy to adapt the program control and the level of concurrency.
	The presented concepts were prototyped as C++ class library, which
	provides a framework for the representation of data Sequences, Functors,
	software agents, and temporal expressions. Based on this library
	an extensive distributed robotic application - a team of soccer playing
	robots - was developed and succesfully employed and tested at different
	international {RoboCup} competitions.},
}