Online stereo camera calibration for automotive vision based on HW-accelerated A-KAZE-feature extraction

Mentzer, Nico; Mahr, Jannik; Payá-Vayá, Guillermo; Blume, Holger

doi:10.1016/j.sysarc.2018.11.003

Cited by 5 publications

(1 citation statement)

References 17 publications

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“…Mentzer et al [16] propose a hardware accelerator for the AKAZE algorithm based on application specific instructionset processors (ASIP) which is used for an advanced driving assistance system. They achieve a frame rate of 20 frames per second which is higher than the results obtained from a conventional processor and consumes less power than the FPGAs.…”

Section: Related Workmentioning

confidence: 99%

Real-time FPGA-based implementation of the AKAZE algorithm with nonlinear scale space generation using image partitioning

Soleimani

Capson

2021

J Real-Time Image Proc

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The first step in a scale invariant image matching system is scale space generation. Nonlinear scale space generation algorithms such as AKAZE, reduce noise and distortion in different scales while retaining the borders and key-points of the image. An FPGA-based hardware architecture for AKAZE nonlinear scale space generation is proposed to speed up this algorithm for real-time applications. The three contributions of this work are (1) mapping the two passes of the AKAZE algorithm onto a hardware architecture that realizes parallel processing of multiple sections, (2) multi-scale line buffers which can be used for different scales, and (3) a time-sharing mechanism in the memory management unit to process multiple sections of the image in parallel. We propose a time-sharing mechanism for memory management to prevent artifacts as a result of separating the process of image partitioning. We also use approximations in the algorithm to make hardware implementation more efficient while maintaining the repeatability of the detection. A frame rate of 304 frames per second for a $$1280 \times 768$$ 1280 × 768 image resolution is achieved which is favorably faster in comparison with other work.

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Section: Related Workmentioning

confidence: 99%