3 accepted papers
LiDAR point cloud data is widely utilized in autonomous driving systems and has significantly improved the 3D detection performance with well-designed deep neural network models. However, due to the complexity of real-world environments and model vulnerability, false detections or malicious attacks…
We propose a lightweight system for stereo-matching using embedded graphic processing units (GPUs). The proposed system overcomes the trade-off between accuracy and processing speed in stereo matching, thus further improving the matching accuracy while ensuring real-time processing. The basic idea i…
The Iterative Closest Points (ICP) algorithm and its variants have been widely applied for 3D point cloud registration which estimates the rigid transformation. As the most computationally intensive step in ICP, nearest neighbor search (NNS) takes up most of the execution time, hindering the practic…