Robert D. Cavin

Larrabee: A Many-Core x86 Architecture for Visual Computing

The Larrabee many-core visual computing architecture uses multiple in-order x86 cores augmented by wide vector processor units, together with some fixed-function logic. This increases the architectures programmability as compared to standard GPUs. The article describes the Larrabee architecture, a software renderer optimized for it, and other highly parallel applications. The article analyzes performance through scalability studies based on real-world workloads.

A Bayesian formulation for 3D articulated upper body segmentation and tracking from dense disparity maps

This paper describes a Bayesian network for 3D articulated upper body segmentation and tracking from video sequences for which both color and depth information are available. In our upper body model the joints are represented as the parent nodes of the body components nodes which include the head, torso or arms. The upper body components are modeled using a set of planar, linear and Gaussian density functions. The model described in this paper segments and tracks accurately the upper body in different illumination conditions and in the presence of partial occlusions and self occlusions. In addition the current approach allows for automatic segmentation of the upper body without any human intervention allowing for further use of the system in hand gesture or human activity recognition.