《BUILDING CHANGE DETECTION BASED ON 3D RECONSTRUCTION》
研究思路： 摘要： 不同時期建築物自動變化檢測對於城市監測、災害評估、地圖更新等具有重要意義。現有的數據源可用於三維幾何模型（如數字表面模型、地理信息系統）和來自衛星或特種飛機的輻射圖像。然而，使用上述方法進行及時變化檢測的費用是非常昂貴的。隨着無人機技術的迅速發展，在低海拔地區利用高分辨率攝像機捕捉城市建築物圖像正在變得越來越便宜。使用這些易獲得的無人機圖像，提出了一種基於三維重建生成變化檢測框
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相關文章
- 1. Image-based 3D Object Reconstruction
- 2. Multi-perspective based 3D pose reconstruction
- 3. Background Prior-Based Salient Object Detection via Deep Reconstruction Residual
- 4. Transferred Deep Learning-Based Change Detection in Remote Sensing Images
- 5. Change Detection Based on Deep Siamese Convolutional Network for Optical Aerial Images
- 6. 3D Object Detection——BEV-based methods
- 7. 3D Object Detection——Voxel based methods
- 8. Detection簡記1-Vehicles Detection Based on Background Modeling
- 9. Camera Calibration and 3D Reconstruction
- 10. vue & @on-change !== on-change @on-change === @change