The Kinect’s Body Part Recognition Algorithm on an FPGA

October 7, 2011
Jason Oberg | MSR Intern

The Microsoft Kinect has received little to no attention by the hardware community, specifically those interested in reconfigurable hardware via field-programmable gate-arrays (FGPAs). This is likely due to both the lack of interfaces and to potential hardware applications. This research project takes a step forward in both directions. We present our findings with attempting to interface the Kinect device to a modern Xilinx MLxxx development board; a common platform for hardware development using FPGAs. In addition, and most importantly, we present a fully-functional hardware implementation of a body part recognition algorithm written entirely in a hardware descriptive language (HDL). The algorithm uses randomized decision trees for computing the probabilistic location of body parts on a human. We present a complete architecture for the design and present a hardware simulation. We predict significant speed-ups over even parallelized software versions of the algorithm and discuss future optimizations.

Speaker Details

Jason Oberg is a third-year PhD student at the University of California, San Diego under Professor Ryan Kastner. He received his Bachelor of Science degree in Computer Engineering from the University of California, Santa Barbara in June 2009. His primary research interests are in security and high-performance computing primarily in an embedded environment using field-programmable gate-arrays (FPGAs).