Authors: Zana Zakaryaie Nejad and Ali Hosseininaveh
ARM-VO is an efficient monocular visual odometry algorithm designed for ARM processors. It uses NEON C intrinsics and multi-threading to accelerate keypoint detection and tracking. Check this video to see the performance on Raspberry Pi 3 and Odroid XU4.
- Cmake
- OpenCV (built with TBB)
git clone https://github.com/zanazakaryaie/ARM-VO.git
cd ARM-VO
cmake .
make
Download the odometry dataset from here. Open a terminal and type:
./ARM_VO pathToData paramsFileName
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ARM-VO recovers the scale if the camera height and pitch angle are provided. Thus, it is not applicable for drones or hand-held cameras.
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The algorithm detects small-inter frame translations and pure rotations using GRIC but it doesn't decompose the estimated homography matrix. Track is lost if the camera rotates too much without translation.
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If you get low FPS, check your power adapter. Raspberry Pi 3 runs ARM-VO at 8 frames per second (averagelly) if powered up with a 5V-2A adapter.
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ARM-VO is a part of six-wheel surveying robot project named MOOR.