MaVirtualSimulationOfMultiCameraOpticalTrackingSystems

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Virtual Simulation of Multi-Camera Optical Tracking Systems

Thesis by: Denis Bakarassov
Advisor: Peter Keitler
Supervision by: Prof. Ph.D. Gudrun Klinker and Prof. Dr. Nassir Navab
Start date: 07/01/2010
Due date: currently in progress

Abstract

Marker-based optical tracking systems are widely used in realtime object tracking, augmented reality, computer-aided medical procedures and industrial applications. Thereby, the position and orientation (pose) of a marker is to be determined in real time. It consists of multiple fiducials that can easily be detected and tracked in the images of multiple cameras. However, in spite of the fact that there exists a number of time-proven technologies and methods of optical tracking, no attempts were made yet to thoroughly and exhaustively investigate the question of uncertainty of object tracking.

The existing works on tracking accuracy estimation are mainly based on the idealized assumption of 2D uncertainties on the CCD of the cameras. They are based on purely analytical considerations and rely on linearization of the mathematical models for error propagation. Effects such as partial or full occlusion of individual fiducials by other fiducials or enviromental objects can not be considered by this technique. They have the major impact on tracking uncertainty, however their influence is poorly understood. This is a crucial issue for such safety-critical areas as medical procedures or industrial metrology, for example.

Therefore the aim of this master thesis work is to develop (design, implement, test and produce) a framework to carry out the computer simulation of an arbitrary optical tracking system, that would enable us to make the exhaustive analysis of its tacking uncertainty and try out the new design decisions without actually building the technical prototype.

The proposed simulation framework practically allows to test the arbitrary tracking algorithms without the need for additional analysis of the underlying functional models. The framework would allow parametrization of the concrete setup, perform the efficient simulation of operation of the tracking system (which involves virtual laboratory setup, generation of artificial camera images, motion recognition of fiducial positions and marker poses),and the technique of Monte-Carlo to investigate the propagation of errors; and finally provide the results that could be easily evaluated with the aid of existing tools of statistical data processing.

The workflow implies the full lifecycle of development of software for scientific computing simulation, starting from modelling and software engineering design, efficient implementation and bridging to the existing tracking algorithms, and thorough testing and cross-validation versus the empiric measurements by the chosen IR multi-camera optical tracking system and the FARO high-precision mechanical measurement arm. The thesis will be concluded by the analysis and scientific visualization of the precision achieved with the proposed simulation framework.

Students.ProjectForm
Title: Virtual Simulation of Multi-Camera Optical Tracking Systems
Abstract: Marker-based optical tracking systems are widely used in realtime object tracking, augmented reality, computer-aided medical procedures and industrial applications. Thereby, the position and orientation (pose) of a marker is to be determined in real time. It consists of multiple fiducials that can easily be detected and tracked in the images of multiple cameras. However, in spite of the fact that there exists a number of time-proven technologies and methods of optical tracking, no attempts were made yet to thoroughly and exhaustively investigate the question of uncertainty of object tracking. The existing works on tracking accuracy estimation are mainly based on the idealized assumption of 2D uncertainties on the CCD of the cameras. They are based on purely analytical considerations and rely on linearization of the mathematical models for error propagation. Effects such as partial or full occlusion of individual fiducials by other fiducials or enviromental objects can not be considered by this technique. They have the major impact on tracking uncertainty, however their influence is poorly understood. This is a crucial issue for such safety-critical areas as medical procedures or industrial metrology, for example. Therefore the aim of this master thesis work is to develop (design, implement, test and produce) a framework to carry out the computer simulation of an arbitrary optical tracking system, that would enable us to make the exhaustive analysis of its tacking uncertainty and try out the new design decisions without actually building the technical prototype. The proposed simulation framework practically allows to test the arbitrary tracking algorithms without the need for additional analysis of the underlying functional models. The framework would allow parametrization of the concrete setup, perform the efficient simulation of operation of the tracking system (which involves virtual laboratory setup, generation of artificial camera images, motion recognition of fiducial positions and marker poses),and the technique of Monte-Carlo to investigate the propagation of errors; and finally provide the results that could be easily evaluated with the aid of existing tools of statistical data processing. The workflow implies the full lifecycle of development of software for scientific computing simulation, starting from modelling and software engineering design, efficient implementation and bridging to the existing tracking algorithms, and thorough testing and cross-validation versus the empiric measurements by the chosen IR multi-camera optical tracking system and the FARO high-precision mechanical measurement arm. The thesis will be concluded by the analysis and scientific visualization of the precision achieved with the proposed simulation framework.
Student: Denis Bakarassov
Director: Gudrun Klinker, Nassir Navab
Supervisor: Peter Keitler
Type: Master Thesis
Area: Computer Vision, Industrial Augmented Reality
Status: finished
Start: 2010/07/01
Finish: 2010/11/30
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