全文翻譯Multi-view point cloud registration with adaptive convergence threshold and its application in 3
具備自適應收斂閾值的多視點雲配準及其在3D模型檢索中的應用web 概要： 多視點雲註冊是人工智能和多媒體技術社區中的熱門話題。在本文中，咱們提出了一種新穎的框架，該框架可使用具備自適應收斂閾值的多視點雲配准算法重建3D模型，並將其隨後應用於3D模型檢索。迭代最近點（ICP）算法是經過自適應收斂閾值實現的，而且進一步與運動平均算法相結合來註冊多視點雲數據。在註冊過程以後，將爲3D模型檢索設計應用程序
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相關文章
- 1. 翻譯和理解：Deep Closest Point: Learning Representations for Point Cloud Registration
- 2. 文獻 Multiview Generative Adversarial Network and Its Application in Pearl Classification閱讀心得——2
- 3. ICP in PCL Registration
- 4. Using Events in Highly Distributed Architectures（待翻譯）
- 5. Collaborative Intelligent Computing System:Theoretical Model with Its Application
- 6. [arXiv 2019] PCRNet: Point Cloud Registration Network using PointNet Encoding
- 7. Deep Closest Point: Learning Representations for Point Cloud Registration && 2019論文筆記
- 8. 【web安全】Xss Exploits and Defense翻譯3
- 9. 論文筆記：Expanded autoencoder recommendation framework and its application in movie recommendation
- 10. Point Cloud 2019