Design and implementation of depth image based real-time human detection

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents the design and implementation of a pipelined architecture and a method for real-time human detection using depth image from a Time-of-Flight (ToF) camera. In the proposed method, we use Euclidean Distance Transform (EDT) in order to extract human body location, and we then use the 1D, 2D scanning window in order to extract human joint location. The EDTbased human extraction method is robust against noise. In addition, the 1D, 2D scanning window helps extracting human joint locations easily from a distance image. The proposed method is designed using Verilog HDL (Hardware Description Language) as the dedicated hardware architecture based on pipeline architecture. We implement the dedicated hardware architecture on a Xilinx Virtex6 LX750 Field Programmable Gate Arrays (FPGA). The FPGA implementation can run 80 MHz of maximum operating frequency and show over 60fps of processing performance in the QVGA (3207times;240) resolution depth image.

Original languageEnglish
Pages (from-to)212-226
Number of pages15
JournalJournal of Semiconductor Technology and Science
Volume14
Issue number2
DOIs
StatePublished - 2014

Keywords

  • Computer vision
  • Human body detection
  • Human body extraction
  • Human interaction system
  • Integrated circuit design
  • Real-time video signal processing

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