no code implementations • 19 Aug 2018 • Yuanxin Ye, Lorenzo Bruzzone, Jie Shan, Francesca Bovolo, Qing Zhu
To address this problem, this paper presents a fast and robust matching framework integrating local descriptors for multimodal registration.
no code implementations • 17 Apr 2019 • Matthew Purri, Jia Xue, Kristin Dana, Matthew Leotta, Dan Lipsa, Zhixin Li, Bo Xu, Jie Shan
The residuals are computed by differencing the sparse-sampled reflectance function with a dictionary of pre-defined dense-sampled reflectance functions.
no code implementations • 19 May 2020 • Bo Xu, Xu Zhang, Zhixin Li, Matt Leotta, Shih-Fu Chang, Jie Shan
For points that belong to the same roof shape, a multi-cue, hierarchical RANSAC approach is proposed for efficient and reliable segmenting and reconstructing the building point cloud.
no code implementations • 19 May 2020 • Zhixin Li, Wenyuan Zhang, Jie Shan
The airborne LiDAR dataset RoofN3D with predefined roof types is used for our test.
no code implementations • 15 Feb 2021 • Anjali Balagopal, Howard Morgan, Michael Dohopoloski, Ramsey Timmerman, Jie Shan, Daniel F. Heitjan, Wei Liu, Dan Nguyen, Raquibul Hannan, Aurelie Garant, Neil Desai, Steve Jiang
A classifier is trained to identify which physician has contoured the CTV from just the contour and corresponding CT scan, to determine if physician styles are consistent and learnable.
no code implementations • 31 Mar 2021 • Yuanxin Ye, Jie Shan, Lorenzo Bruzzone, Li Shen
Moreover, a robust registration method is also proposed in this paper based on HOPCncc, which is evaluated using six pairs of multimodal remote sensing images.