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http://dx.doi.org/10.6109/jkiice.2014.18.10.2443

Conversion Method of 3D Point Cloud to Depth Image and Its Hardware Implementation  

Jang, Kyounghoon (Department of Electronic Engineering, Dong-A University)
Jo, Gippeum (Department of Electronic Engineering, Dong-A University)
Kim, Geun-Jun (Department of Electronic Engineering, Dong-A University)
Kang, Bongsoon (Department of Electronic Engineering, Dong-A University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.10, 2014 , pp. 2443-2450 More about this Journal
Abstract
In the motion recognition system using depth image, the depth image is converted to the real world formed 3D point cloud data for efficient algorithm apply. And then, output depth image is converted by the projective world after algorithm apply. However, when coordinate conversion, rounding error and data loss by applied algorithm are occurred. In this paper, when convert 3D point cloud data to depth image, we proposed efficient conversion method and its hardware implementation without rounding error and data loss according image size change. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.
Keywords
Motion Recognition; Depth Image; 3D Point Cloud; Coordinate Conversion; Hole Filling;
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Times Cited By KSCI : 1  (Citation Analysis)
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