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| May 3
| May 3
| Nazre Batool
| Nazre Batool
|
| Spatial Marked Point Processes in Computer Vision
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|-
| May 10
| May 10
Real time rendering of a massive virtual world requires efficient management of textures, geometric structures, and a variety of visual effects. Despite the recent improvements of the Graphics Processing Units (GPU), the currently available memory space and computation power is still not enough to store and process textures and geometries that are used to represent a high-quality virtual world. One way to overcome this problem is use Clipmap, which is a hardware accelerated approach that manages levels of detail (LOD) for objects, textures, and effects used to render a virtual world.
Real time rendering of a massive virtual world requires efficient management of textures, geometric structures, and a variety of visual effects. Despite the recent improvements of the Graphics Processing Units (GPU), the currently available memory space and computation power is still not enough to store and process textures and geometries that are used to represent a high-quality virtual world. One way to overcome this problem is use Clipmap, which is a hardware accelerated approach that manages levels of detail (LOD) for objects, textures, and effects used to render a virtual world.
===Spatial Marked Point Processes in Computer Vision===
Speaker: Nazre Batool -- Date: May 3, 2012
The computer vision community is very familiar with Markov random field (MRF) modeling for numerous applications. In this talk, I will present an overview of the more general, but less popular, Markov point processes (MPP) and will highlight the connection between MRF and MPP and the advantages of MPP modeling for specific applications. Recently, several versions of MPP called ‘Marked’ point processes have been used in remote sensing/aerial imaging applications. I will discuss some of the applications and finally, present my recent work based on MPP.
