Sound source localization with microphone arrays has received considerable attention as a means for the automated tracking of individuals in an enclosed space and as a necessary component of any general-purpose speech capture and automated camera pointing system. A novel computationally efficient method compared to traditional source localization techniques is proposed and is both theoretically and experimentally investigated in this research. This thesis first reviews the previous work in this area. The evolution of a new localization algorithm accompanied by an array structure for audio signal localization in three dimensional space is then presented. This method, which has similarities to the structure of the eye, consists of a novel hemispherical microphone array with microphones on the shell and one microphone in the center of the sphere. The hemispherical array provides such benefits as 3D coverage, simple signal processing and low computational complexity. The signal processing scheme utilizes parallel computation of a special and novel closeness function for each microphone direction on the shell. The closeness functions have output values that are linearly proportional to the spatial angular difference between the sound source direction and each of the shell microphone directions. Finally by choosing directions corresponding to the highest closeness function values and implementing linear weighted spatial averaging in those directions we estimate the sound source direction. The experimental tests validate the method with less than 3.10 of error in a small office room. Contrary to traditional algorithmic sound source localization techniques, the proposed method is based on parallel mathematical calculations in the time domain. Consequently, it can be easily implemented on a custom designed integrated circuit.

A pose estimation method is proposed for measuring the position and orientation of a biopsy needle. The technique is to be used as a touchless needle guide system for guidance of percutaneous procedures with 4D ultrasound. A pair of uncalibrated, light-weight USB cameras are used as inputs. A database is prepared offline, using both the needle line estimated from camera-captured images and the true needle line recorded from an independent tracking device. A nonparametric learning algorithm determines the best fit model from the database. This model can then be used in real-time to estimate the true position of the needle with inputs from only the camera images. Simulation results confirm the feasibility of the method and show how a small, accurately made database can provide satisfactory results. In a series of tests with cameras, we achieved an average error of 2.4mm in position and 2.61° in orientation. The system is also extended to real ultrasound imaging, as the two miniature cameras capture images of the needle in air and the ultrasound system captures a volume as the needle moves through the workspace. A new database is created with the estimated 3D position of the needle from the ultrasound volume and the 2D position and orientation of the needle calculated from the camera images. This study achieved an average error of 0.94 mm in position and 3.93° in orientation.

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The Kalman filter algorithm can be applied as a recursive estimator of the state of a dynamic system described by a linear difference equation. Given discrete measurements linearly related to the state of the system, but corrupted by white Gaussian noise, the Kalman filter estimate of the system is statistically optimal with respect to a quadratic function of the estimate error. The first objective of this paper is to give deep enough insight into the mathematics of the Kalman filter algorithm to be able to choose the correct type of algorithm and to set all the parameters correctly in a basic application. This description also includes several examples of different approaches to derive and to explain the Kalman filter algorithm. In addition to the mathematical description of the Kalman filter algorithm this paper also provides an implementation written in MATLAB. The objective of this part is to correctly replicate the target tracker used in the surveillance radar PS-90. The result of the implementation is evaluated using a simulated target programmed to have an aircraft-like behaviour and done without access to the actual source code of the tracker in the PS-90 radar

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Tracking of an object in six degrees-of-freedom (DOF) produces a position and orientation estimate of the object as it moves in 3D space. This thesis investigates the design and implementation of a prototype optical 6 DOF tracking system. Although optical scanners potentially have issues regarding occlusion they have advantages over electromagnetic scanners in that they can be used without distortion near ferromagnetic materials and can have large working volumes. This thesis focuses on the design of a small camera module named the ‘Black Spot’ that forms part of the overall tracking system. This module is capable of tracking the locations of up to 27 LED markers at 60 frames/s as the module moves in space. These markers provide fixed reference points that are utilised by the tracking system. A number of these modules will, in future revisions of the system, be clustered closely together forming a tracking hub. In this research this hub has been partially implemented in software on a PC. This software implements a ‘pose estimation’ algorithm that iteratively refines the location and position of the camera modules. Results from testing three Black Spot modules indicates that the locations of the LED markers can be determined very precisely using a centroid calculation. Standard deviations of better than 0.01 pixels have been recorded using these modules. The pose estimation algorithm has been tested revealing the need for a better minimisation algorithm. It is recommended that a bundle adjustment algorithm is used in the future to refine the world model used by the hub. The calibration of the system is a task for future research.

Radio Frequency Identification (RFID) technology has been widely adopted by different industries for various purposes. While implementing a RFID system for personnel tracking in an industrial environment, such as a hospital, the tracking accuracy is not always satisfactory due to incorrect placement of RFID hardware, coarse system configuration or environment. This thesis proposes comprehensive optimization methods for improving the tracking accuracy of a RFID system for personnel tracking. The improvement is achieved from four perspectives including RFID data cleaning, experimental design, data fusion and simulation modeling. This research is based on a case study carried out in a local community hospital where a RFID system for personnel tracking has been implemented. Through applying the optimization methods, the tracking accuracy of the RFID system has been improved to 87.33%. The thesis provides a guideline for the hospital and other similar application environment to implement improvement methods on a RFID tracking system.

The effect hand action representations have on language processing was investigated using eye-tracking techniques. Subjects were shown an image of a hand action and asked to hold the action in working memory while reading a sentence, which described an actor lifting, or using an object. The displayed hand actions were related to either a functional (using) or volumetric (lifting) interaction with an object that matched or did not match the object mentioned in the sentence. A neutral condition was also used which displayed a black circle instead of a hand action. No significant difference was found between any of the five working memory conditions for gaze duration, probability of word skipping, and several other dependent measures utilized in the study. A significant difference was found for gaze duration when the conditions were restricted. Shorter gaze duration was observed for the hand action congruent to both the context and the object mentioned in the sentence and longer gaze duration was observed for the hand action congruent to only the sentence context. Some possible explanations of the results are that subjects may not have encoded the hand actions as action representations, or that hand actions represented in working memory have no effect on sentence processing. / Graduate / 0633