activity
20182021
most cited3D Point Cloud Denoising via Bipartite Graph Approximation and Reweighted Graph Laplacian

12 citations · 12 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SP2021

Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment

Chinthaka Dinesh, Gene Cheung, Ivan Bajic

3D point cloud (PC) -- a collection of discrete geometric samples of a physical object's surface -- is typically large in size, which entails expensive subsequent operations like v…

eess.SP2019

3D Point Cloud Super-Resolution via Graph Total Variation on Surface Normals

Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic

Point cloud is a collection of 3D coordinates that are discrete geometric samples of an object's 2D surfaces. Using a low-cost 3D scanner to acquire data means that point clouds ar…

eess.SP201812 cited

3D Point Cloud Denoising via Bipartite Graph Approximation and Reweighted Graph Laplacian

Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic

Point cloud is a collection of 3D coordinates that are discrete geometric samples of an object's 2D surfaces. Imperfection in the acquisition process means that point clouds are of…

eess.SP2018

Fast 3D Point Cloud Denoising via Bipartite Graph Approximation & Total Variation

Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic +1

Acquired 3D point cloud data, whether from active sensors directly or from stereo-matching algorithms indirectly, typically contain non-negligible noise. To address the point cloud…

eess.SP2018

Adaptive Non-Rigid Inpainting of 3D Point Cloud Geometry

Chinthaka Dinesh, Ivan V. Bajic, Gene Cheung

In this letter, we introduce several algorithms for geometry inpainting of 3D point clouds with large holes. The algorithms are examplar-based: hole filling is performed iterativel…