
Be the first to like this
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.
Published on
"Texture" provides the perceptual information about the surface, nature etc. about the visual objects. Study in texture learning and synthesis with a mathematical model will hopefully provide us the mathematical nature of visual perceptiveness.
On the other hand, Markov Random Field, nonparametric density estimation and their applications in the real world problems, are becoming popular in both research and industrial fields. The reason for this popularity is because of the mathematical models have more robustness, flexibility and simplicity.
The research problems (given this background) are order estimation and large computational complexity. In my PhD thesis I have tried to solve these issues for the application in homogeneous texture synthesis.
Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics.
Be the first to comment