Real-time 3D reconstruction for FPGAs: A case study for evaluating the performance, area, and programmability trade-offs of the Altera OpenCL SDK

Embedding real-time 3D reconstruction of a scene from a low-cost depth sensor can improve the development of technologies in the domains of augmented reality, mobile robotics, and more. However, current implementations require a computer with a powerful GPU, which limits its prospective applications with low-power requirements. To implement low-power 3D reconstruction we embedded two prominent algorithms of 3D reconstruction (Iterative Closest Point and Volumetric Integration) on an Altera Stratix V FPGA by using the OpenCL language and the Altera OpenCL SDK. In this paper, we present our application and evaluation of the Altera tool in terms of performance, area, and programmability trade-offs. We have verified that OpenCL can be a viable method for developing FPGA applications by modifying an open-source version of the Microsoft KinectFusion project to run partially on a FPGA.

[1]  Doris Chen,et al.  Invited paper: Using OpenCL to evaluate the efficiency of CPUS, GPUS and FPGAS for information filtering , 2012, 22nd International Conference on Field Programmable Logic and Applications (FPL).

[2]  Marc Levoy,et al.  A volumetric method for building complex models from range images , 1996, SIGGRAPH.

[3]  Andrew W. Fitzgibbon,et al.  KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera , 2011, UIST.

[4]  Andrew W. Fitzgibbon,et al.  KinectFusion: Real-time dense surface mapping and tracking , 2011, 2011 10th IEEE International Symposium on Mixed and Augmented Reality.

[5]  Michael A. Greenspan,et al.  A high speed iterative closest point tracker on an FPGA platform , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[6]  Implementing FPGA Design with the OpenCL Standard , 2010 .