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Area of Science:

  • Computer Vision
  • Embedded Systems Engineering
  • Digital Image Processing

Background:

  • Video stabilization is crucial for consumer cameras but computationally intensive.
  • High memory access requirements hinder real-time implementation on low-cost camera System-on-Chips (SoCs).
  • Reducing memory usage is critical for efficient camera hardware design.

Purpose of the Study:

  • To propose an efficient structure and layout method for video stabilization on low-end hardware.
  • To minimize shared memory access in real-time video stabilization.
  • To enable cost-effective development of real-time video stabilization devices.

Main Methods:

  • A novel parasitic placement of sub-components within existing processing blocks.
  • Data reuse from other processing blocks, avoiding direct shared memory access.
  • Implementation focused on reducing memory access for low-end hardware.

Main Results:

  • The proposed method significantly reduces memory access by 21.1 times compared to straightforward approaches.
  • Achieves sufficient performance for real-time devices on lower-cost camera hardware.
  • While not surpassing post-processing quality, it offers practical benefits for embedded systems.

Conclusions:

  • The presented method efficiently implements video stabilization for resource-constrained hardware.
  • It effectively lowers the cost of camera hardware for real-time applications.
  • This approach addresses the critical issue of memory usage in embedded camera systems.