Dr Cara MacNish, cara@csse.uwa.edu.au

Cara has studied Electrical Engineering (UWA), Artificial Intelligence (University of Cambridge, UK) and Psychology (UWA) and has held lecturships in Computer Science Departments at the University of York (UK) and at UWA since 1992. She has been working in Artificial Intelligence - that is, engineering biologically-inspired solutions to computational problems - and allied disciplines for almost 20 years.

The aim of these projects is to provide you with interesting technical problems (which you will want to write about in your thesis) combined with the satisfaction of building something that you can see working (which you will want to show off in your presentation).

Projects

Projects offered for 2009 focus on applying Comptutational Intelligence techniques to problems in vision processing and interpretation. Some projects may be co-supervised with other members of staff or research students.

1. Computational Intelligence Techniques for Navigation

   The aim of this project is to investigate the use of evolutionary and allied dynamical optimisation techniques for navigating a terrain, for example an autonomous vehicle following a road or path.

2. Driving a Racing Car Simulator using Visual Data

   Similar to the above, but focussing on the TORCS racing car simulator. Current attempts to learn bots for the simulator rely on sensor data available to the bots. This is very different to the data available to human players. The aim of this project is to learn to drive using the visual data available to humans.

3. Investigation of Fitness Landscapes for Text Location in Images

   Location of distinctive items in images could be of great use to people with visual impairments as well as in robotics. This project looks at using a range of functions or transforms to generate landscapes from image features suitable for robust high-dimensional evolutionary style searches for object (particularly text) location and tracking.

4. Computational Intelligence Techniques for Pose Estimation

   Like the above project this one is concerned with location and tracking using CI search techniques, however this project focuses on fitting multiple degree of freedom "avatars" to human pose estimation and tracking.

5. Compositonal Pattern Producing Networks for Object Identification and Tracking

   Rather than using traditional functions and transformations for feature extraction, this project investigates the use of new "neural network" like technique for pattern generation and matching, called compositional pattern producing networks.

6. Computational Intelligence Techniques for Searching Video Footage

   The ability to find specific items in video footage is important in a range of applications from security to web searching. The task is often made more difficult by the poor quality of footage and issues such as occlusion and deformation. The aim of this project is to investigate the use of Computational Intelligence search techniques to develop robust approximate approaches for searching difficult video.

7. Investigating the AdaBoost Approach to Learning

   Whereas many traditional machine learning techniques seek to generate a single, high accuracy decision or classification from the data, the AdaBoost approach instead generates classifications from a compound sequence of many simple or less discriminating classifiers. It has been argued that this approach can result in improved performance. This project aims to test this approach in a practical domain such as those above.

Previous Project Proposals

References and Past Projects

Illustrative References

Stanley, K., "Compositional pattern producing networks: A novel abstraction of development", Genetic Programming and Evolvable Machines, 8, 131-162, 2007

Kumazawa, I., "Target tracking by matching a shape represented by a tree of sigmoid functions", Pattern Recognition Letters, 21, 661-675, 2000

Illustrative Past Projects

Carey, L., Computational Intelligence as an Object Tracking Paradigm for Game Agents, Graduate Diploma in Engineering Thesis, CSSE, UWA, 2008

Cristobal, T., Discrimination of a Hand from a Face using Template Matching, Honours Thesis, CSSE, UWA, 2003