skip to main content
10.1145/2435264.2435319acmconferencesArticle/Chapter ViewAbstractPublication PagesfpgaConference Proceedingsconference-collections
poster

High performance architecture for object detection in streamed video (abstract only)

Published: 11 February 2013 Publication History

Abstract

Object detection is one of the key tasks in computer vision. It is computationally intensive and it is reasonable to accelerate it in hardware. The possible benefits of the acceleration are reduction of the computational load of the host computer system, increase of the overall performance of the applications, and reduction of the power consumption. We present novel architecture for multi-scale object detection in video streams. The architecture uses scanning window classifiers produced by WaldBoost learning algorithm, and simple image features. It employs small image buffer for data under processing, and on-the-fly scaling units to enable detection of object in multiple scales. The whole processing chain is pipelined and thus more image windows are processed in parallel. We implemented the engine in Spartan 6 FPGA and we show that it can process 640x480 pixel video streams at over 160 frames per second without the need of external memory. The design takes only a fraction of resources, compared to similar state of the art approaches.

Cited By

View all
  • (2014)Comparison of Appearance-Based and Geometry-Based Bubble DetectorsComputer Vision and Graphics10.1007/978-3-319-11331-9_73(610-617)Online publication date: 2014

Index Terms

  1. High performance architecture for object detection in streamed video (abstract only)

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      FPGA '13: Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
      February 2013
      294 pages
      ISBN:9781450318877
      DOI:10.1145/2435264

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 11 February 2013

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. FPGA
      2. local binary patterns
      3. local rank functions
      4. object detection
      5. stream processing
      6. waldboost

      Qualifiers

      • Poster

      Conference

      FPGA '13
      Sponsor:

      Acceptance Rates

      Overall Acceptance Rate 125 of 627 submissions, 20%

      Upcoming Conference

      FPGA '25

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)0
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 18 Feb 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2014)Comparison of Appearance-Based and Geometry-Based Bubble DetectorsComputer Vision and Graphics10.1007/978-3-319-11331-9_73(610-617)Online publication date: 2014

      View Options

      View options

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media