mlsanityData to 7 Oct 2026

Deep Learning Computer Vision Algorithms for Real-time UAVs On-board Camera Image Processing

arXiv 2211.01037 ↗First posted 2 Nov 2022cs.CVcited by 1

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Abstract (arXiv)

This paper describes how advanced deep learning based computer vision algorithms are applied to enable real-time on-board sensor processing for small UAVs. Four use cases are considered: target detection, classification and localization, road segmentation for autonomous navigation in GNSS-denied zones, human body segmentation, and human action recognition. All algorithms have been developed using state-of-the-art image processing methods based on deep neural networks. Acquisition campaigns have been carried out to collect custom datasets reflecting typical operational scenarios, where the peculiar point of view of a multi-rotor UAV is replicated. Algorithms architectures and trained models performances are reported, showing high levels of both accuracy and inference speed. Output examples and on-field videos are presented, demonstrating models operation when deployed on a GPU-powered commercial embedded device (NVIDIA Jetson Xavier) mounted on board of a custom quad-rotor, paving the way to enabling high level autonomy.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 45 of its 59 references that are in the map. First posted on arXiv 2 Nov 2022.

Builds on

45 of 59 references.

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