• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. A configurable framework for hough-transform-based embedded object recognition systems
 
  • Details
  • Full
Options
2018
Conference Paper
Title

A configurable framework for hough-transform-based embedded object recognition systems

Abstract
Real-time object recognition on low-power embedded devices is a widely requested task, needed in manifold applications. However, it is still a demanding challenge to achieve desired performance goals. For example, for advanced driver assistance systems (ADAS) or autonomously driven cars, object recognition and lane detection are indispensable tasks. Another field of application is the continuous retrieval of the construction progress on-site for validation of the construction site status, by detecting installed components using a given CAD model. This paper presents a framework for highly customizable object detection systems implemented on a single heterogeneous computing chip leveraging FPGA logic and standard processors. The FPGA logic is used to implement a custom variation of the Hough Transform and further image processing tasks efficiently. The dedicated logic is supplemented with a software stack, which consists of a Linux operating system, including hardware access drivers, as well as high-level libraries like OpenCV and Robot Operating System (ROS) - all running on the same device. The capabilities of the system are demonstrated for three application scenarios, namely race track recognition, lane recognition and object detection tasks performed within a construction assistance system.
Author(s)
Sarcher, Julian
Univ. of Applied Sciences Augsburg
Scheglmann, Christian
Univ. of Applied Sciences Augsburg
Zoellner, Alexander
Univ. of Applied Sciences Augsburg
Dolereit, Tim  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Schäferling, Michael
Univ. of Applied Sciences Augsburg
Vahl, Matthias  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kiefer, Gundolf
Univ. of Applied Sciences Augsburg
Mainwork
IEEE 29th International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2018  
Conference
International Conference on Application-Specific Systems, Architectures and Processors (ASAP) 2018  
DOI
10.1109/ASAP.2018.8445086
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • heterogeneous computing

  • object recognition

  • computer vision

  • Lead Topic: Digitized Work

  • Research Line: Computer vision (CV)

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024