Name
Title | ||
|---|---|---|
Reconfigurable Multi-Access Pattern Vector Memory For Real-Time ORB Feature Extraction |
Abstract | ||
|---|---|---|
This work presents an on-chip memory subsystem envisioned for real-time applications performing Oriented FAST and Rotated Brief (ORB) feature extraction for Simultaneous Localization and Mapping (SLAM) systems. For autonomous navigation of battery-powered devices, feature-based SLAM is a computationally frugal alternative to direct methods. This paper thoroughly analyses ORB multiple memory access patterns, exploring possible systematic parallelism and hardware-biased algorithmic enhancements, alleviating requirements on bandwidth and reducing redundant accesses. Enabling those, a suitable multi-bank parallel memory featuring run-time reconfigurable address generation, image allotment, and close-to-memory data-shuffling is proposed. As case study, a 30 Frames-Per-Second (FPS) VGA-resolution ORB-capable 8-bank memory is evaluated using 22 FDX technology, running at 909 MHz, with a negligible area overhead of 0.3%, reducing operand accesses between 54 - 160x relative to Sudoku-like and scalar memories. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISCAS51556.2021.9401698 | 2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) |
Keywords | DocType | ISSN |
vision-based SLAM, Feature Extraction, ORB, programmable multiple memory access patterns | Conference | 0271-4302 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas Ferreira | 1 | 0 | 0.34 |
| Steffen Malkowsky | 2 | 37 | 4.80 |
| Patrik Persson | 3 | 0 | 0.34 |
| Karl Astrom | 4 | 0 | 0.34 |
| Liang Liu | 5 | 95 | 18.47 |