MCL Director, Professor C.-C. Jay Kuo, gave an opening keynote at the IEEE International Conference on Visual Communications and Image Processing (VCIP) on December 2, 2020. The meeting would originally be held from December 1-4, 2020, in Macau. However, due to the COVID-19 pandemic, it became a virtual one. The keynote is titled with “Interpretable and Effective Learning for 3D Point Cloud Registration, Classification and Segmentation.” Here is the abstract:

“3D point cloud analysis and processing find numerous applications in computer-aided design, 3D printing, autonomous driving, etc. Most state-of-the-art point cloud processing methods are based on convolutional neural networks (CNNs). Although they outperform traditional methods in terms of accuracy, they demand heavy supervision and higher training complexity. Besides, they lack mathematical transparency. In this talk, I will present three interpretable and effective machine learning methods for 3D point cloud registration, classification and segmentation, respectively. First, an unsupervised registration method that extracts salient points for matching is presented. Second, an unambiguous way to order points sequentially in a point cloud set is developed. Then, their spatial coordinates can be treated as geometric attributes of 1D data array. This idea facilitates the classification task. Third, for the segmentation task, we show how to leverage prior knowledge on point clouds to derive an intuitive and effective segmentation method. Extensive experiments are conducted to demonstrate the performance of the three new methods. I will also provide performance benchmarking between these interpretable methods and deep learning methods.”

The keynote was well attended with many questions during the 10-minute Q&A session. Professor Kuo’s keynote was sponsored by Tencent and called the Tencent Keynote Speech.