"Active Modeling Through Proactive Sensing"
![](https://www.umiacs.umd.edu/sites/default/files/styles/medium/public/chen.png?itok=xLjhDf4u)
Location: A.V. Williams Building, Rm. 2120
Speaker:
Baoquan Chen, National Changjiang Endowed Chair Professor and executive director of the Center on Frontiers of Computing Studies (CFCS), Peking University
Abstract:
With the advent of 3-D sensors, e.g., depth cameras and laser scanners, depth images or point clouds are becoming a prevalent raw representation of the real-world environments.
Generating full geometry representations from these discrete data remains a significant challenge. The reasons for this are two-fold: (1) the raw data is usually sparse, noisy, and incomplete, and (2) the complexity and large scale of the real-world scenes put restrictions on user interaction, thus requiring a fully-automated process.
In this talk, I will introduce our recent work on modeling with knowledge guidance, resulting in semantics information, and closing the loop with proactive data sensing.
Speaker Bio:
Baoquan Chen is a National Changjiang Endowed Chair Professor and executive director of the Center on Frontiers of Computing Studies (CFCS) at Peking University. He is the chief scientist of Beijing Innovation Center for Future Visual Entertainments, Beijing Film Academy.
His research interests include computer graphics and visualization.
Chen is the recipient of an NSF CAREER award (2003), University of Minnesota McKnight Land-Grant Professorship (2004), IEEE Visualization Best Paper Award (2005), and the Chinagraph Outstanding Achievement Award (2014).
He was previously dean of the School of Computer Science and Technology, Shandong University (2013-2018); founding director of the Visual Computing Research Center; Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (2008-2013); and a faculty member at the University of Minnesota at Twin Cities (2000-2008).
Chen received his doctorate in computer science from SUNY at Stony Brook in 1999.