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Related Experiment Video

Updated: May 24, 2026

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

Published on: April 8, 2019

FPGA implementation for real-time background subtraction based on Horprasert model.

Rafael Rodriguez-Gomez1, Enrique J Fernandez-Sanchez, Javier Diaz

  • 1Department of Computer Architecture and Technology, ETS Computer Engineering and Telecommunications, University of Granada, C/ Periodista Daniel Saucedo s/n, E18071 Granada, Spain. rrodriguez@atc.ugr.es

Sensors (Basel, Switzerland)
|February 28, 2012
PubMed
Summary
This summary is machine-generated.

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This study introduces a novel FPGA architecture for efficient background subtraction in video surveillance. The design optimizes resource usage and performance, enabling real-time object detection in limited environments.

Area of Science:

  • Computer Vision
  • Embedded Systems
  • Hardware Acceleration

Background:

  • Background subtraction is crucial for video surveillance, identifying moving objects from static camera feeds.
  • It is computationally intensive, posing challenges for resource-constrained systems.
  • Existing methods often involve trade-offs between accuracy, performance, and resource utilization.

Purpose of the Study:

  • To propose a novel embedded Field-Programmable Gate Array (FPGA) architecture for efficient background subtraction.
  • To extend the model for shadow detection and enhance moving object segmentation quality.
  • To analyze resource consumption and performance on Xilinx Spartan3 FPGAs.

Main Methods:

  • Development of a hardware-friendly modified model for background extraction.
Keywords:
FPGAsperformance analysisreal time image processingreconfigurable architecturesvideo surveillance

Related Experiment Videos

Last Updated: May 24, 2026

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

Published on: April 8, 2019

  • Integration of shadow detection and improved segmentation capabilities.
  • Implementation and evaluation on Spartan3 Xilinx FPGAs, comparing against existing literature.

    • Main Results:

    • Achieved a frequency of 66.5 MHz at 32.8 frames per second for 1024x1024 resolution.
    • Utilized less than 65% of resources on a low-cost Spartan-3A FPGA (XC3SD3400).
    • Estimated power consumption of 5.76 W, demonstrating a balance of accuracy, performance, and resource efficiency.

    Conclusions:

    • The proposed FPGA architecture offers an effective solution for background subtraction in resource-limited environments.
    • It presents a favorable trade-off between accuracy, performance, and resource utilization.
    • The extended model enhances surveillance capabilities by including shadow detection and improved segmentation.