Thomas Methven
Texture Lab,
School of Mathematical and Computer Science,
Heriot-Watt University, Edinburgh, EH14 4AS
tm112 at hw dot ac dot uk
+44 (0)131 451 4166
Research Interests
Wiimote Tracking
Before joining the Texture Lab, I completed an award-winning MEng Project using the Wiimote to track a user’s fingers.
How Finger-Tracking Works
This project involved created several different prototype applications and testing them with school children to see whether finger tracking might be a popular new input method. During this project, two new programs were created, one which allowed for users to finger paint on the screen and the other which allowed them to play a virtual piano (as well as a couple of piano-based games). The piano application was developed further and proved very popular when tested again, especially when used in pairs.
From this, I gained a in-depth knowledge of how the Wiimote worked and possibly avenues of future work.
Surface/Fabric Properties
In association with my colleague, Pawel Orzechowski and the EPSRC funded Digital Sensoria project, I helped create and compile a taxonomy of descriptive words for fabrics which was drawn from non-experts. Participants performed a free grouping experiment with 78 fabric words to create a taxonomy we could use to test property transmission. 11 groups were found by ‘cutting’ the dendrogram created from the similarity results. In addition, participants identified which word from each group best represented that group.
Results from these experiments are shown below.
Word Sorting Dendrogram (Click for full-size)
Word Sorting Cloud (Click for full-size)
Reaction-Diffusion Patterns
To investigate the possibility of using Reaction-Diffusion Patterns as a way of generating naturalistic surfaces for my research, I created a simple application which would allow me to create them. This application lets users watch as the patterns grow and alter the input values, as well as providing a couple of interesting pre-set values.
Reaction Diffusion Standalone Toolbox Example
Binocular Vision and Gloss
The current focus of my research is on binocular perception of gloss with rough surfaces. Currently, I am working on created realistic, accurately lit, binocular image pairs which will allow me to examine the interplay of Lambertian reflectance and specular highlights on surface shape, depth and realism perception.
An example of a surface's Lambertian shading and specular highlights
For example, the image below is a correct stereo pair (i.e. all the disparity information is correct):
Correct Stereo Pair (Suitable for cross-eyed fusion, Click for full-size)
The image below, however, is incorrect. While the gloss has correct disparity, the surfaces itself appears flat:
Incorrect Stereo Pair (Suitable for cross-eyed fusion, Click for full-size)
Conferences and Publications
- Multimodal Presentation of Complex Surfaces
- 2010 High Value Manufacturing IMRC Conference – Poster
- Does Highlight Disparity Improve Perception of Gloss on Rough Surfaces?
- 2011 AVA/BMVA Spring Meeting on Biological and Computer Vision – Poster
Extras
3D version of a word cloud where the height value is calculated by the luminance per pixel. Interactive version via shoogleit.com: 3D Word Cloud
