See Behind Walls in Real-time Using Aerial Drones and Augmented Reality
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Abstract (arXiv)
This work presents ARD2, a framework that enables real-time through-wall surveillance using two aerial drones and an augmented reality (AR) device. ARD2 consists of two main steps: target direction estimation and contour reconstruction. In the first stage, ARD2 leverages geometric relationships between the drones, the user, and the target to project the target's direction onto the user's AR display. In the second stage, images from the drones are synthesized to reconstruct the target's contour, allowing the user to visualize the target behind walls. Experimental results demonstrate the system's accuracy in both direction estimation and contour reconstruction.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 28 references that are in the map. First posted on arXiv 17 Oct 2024.
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7 of 28 references.
References · 7
- 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
- 2016DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFscited by 3,241
- 2015Holistically-Nested Edge Detectioncited by 592
- 2023FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularizationcited by 311
- 2023SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesiscited by 247
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