Probabilistic Fusion of Depth Maps with Local Variance Estimation
Author:
Affiliation:
1. Institute for Applications of Machine Learning and Intelligent Systems, University of Applied Science Munich,Dept. of Electrical Engineering and Information Technology,Munich,Germany,80335
Funder
BMBF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10324456/10324848/10325039.pdf?arnumber=10325039
Reference13 articles.
1. Probabilistic Fusion of Depth Maps With a Reliable Estimation of the Local Reconstruction Quality
2. ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception;dong;IEEE Transactions on Pattern Analysis and Machine Intelligence,2021
3. Analysis and Noise Modeling of the Intel RealSense D435 for Mobile Robots
4. RoutedFusion: Learning Real-Time Depth Map Fusion
5. Analyzing the potential of a time-of-flight depth sensor for assembly assistance;niedermayr;IEEE International Symposium on Multimedia,2021
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1. Probabilistic Closed-Loop Active Grasping;IEEE Robotics and Automation Letters;2024-04
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