… -based data fusion approaches that leverage both image and point cloud. This review gives
… and point cloud data processing. Followed by in-depth reviews of camera-LiDAR fusion …

… for accurate point-wise segmentation of large-scale point clouds, we develop a deep fusion
… “mini-PointNet” structure for point cloud representation and a novel fusion module (Fig. 2) for …

… We denote X as an arbitrary representation of a point cloud, and any form of point cloud
representation X can be seen as a mapping of the original points P. To note that,“projection” …

… task of point cloud segmentation to show the effectiveness and benefits of our fusion method.
… and applying an ImageNet CNN for early fusion, eg [11] or intermediate fusion, eg [13], ham…

… matrix needed to align the source point cloud with target point cloud. This resultant point
cloud, source point cloud aligned, will be the target point cloud in the next mapping iteration. …

… vision, this work proposes a real-time vehicle detection algorithm which fuses vision and lidar
point cloud … by the grid projection method using the lidar point cloud information. Then, the …

… reconstructed point cloud as G and the LiDAR reconstructed point cloud as L. The point cloud
patches in G are defined as PG = 1pg1 ,pg2 ,pg3 ··· pgu l. In the same manner, point cloud …

… the rigid transformation from the source point cloud to the template point cloud. Experiments
on the synthetic … His research interests include computer vision and point cloud processing. …

… Optical imagery and Light Detection And Ranging (LiDAR) point cloud are two types of major
data sources in the fields of photogrammetry and remote sensing, computer vision, pattern …

… Multisensory fusion involving cameras, LiDARs and radar, has extensively been employed
… -D point cloud object detection, and object detection based on laser and vision fusion. Image …