Monday January 27, 2020
3D/4D NN-based Data Processing
Session Chair:
Tyler Bell, University of Iowa (United States)
8:45 – 10:10 AM
Grand Peninsula A
8:45
Conference Welcome
8:503DMP-002
Deadlift recognition and application based on multiple modalities using recurrent neural network, Shih-Wei Sun1, Ting-Chen Mou2, and Pao-Chi Chang2; 1Taipei National University of the Arts and 2National Central University (Taiwan)
9:103DMP-003
Learning a CNN on multiple sclerosis lesion segmentation with self-supervision, Alexandre Fenneteau1,2,3, Pascal Bourdon2,3, David Helbert2,3, Christine Fernandez Maloigne2,3, Christophe Habas1,3, and Rémy Guillevin3,4,5; 1Quinze-Vingts Hospital, 2XLIM Laboratory, University of Poitiers, 3I3M, Common Laboratory CNRS-Siemens, University and Hospital of Poitiers, 4Poitiers University Hospital, and 5DACTIM-MIS/LMA Laboratory University of Poitiers (France)
9:303DMP-004
Action recognition using pose estimation with an artificial 3D coordinates and CNN, Jisu Kim and Deokwoo Lee, Keimyung University (Republic of Korea)
9:50
3DMP Q&A Session Discussion
10:10 – 10:50 AM Coffee Break
3D/4D Measurement and Processing
Session Chair:
Tyler Bell, University of Iowa (United States)
10:50 AM – 12:10 PM
Grand Peninsula A
10:503DMP-034
Variable precision depth encoding for 3D range geometry compression, Matthew Finley and Tyler Bell, University of Iowa (United States)
11:103DMP-035
3D shape estimation for smooth surfaces using grid-like structured light patterns, Yin Wang and Jan Allebach, Purdue University (United States)
11:303DMP-036
Quality assessment for 3D reconstruction of building interiors, Umamaheswaran Raman Kumar, Inge Coudron, Steven Puttemans, and Patrick Vandewalle, Katholieke Universiteit Leuven (Belgium)
11:50
3DMP Q&A Session Discussion
12:30 – 2:00 PM Lunch
PLENARY: Frontiers in Computational Imaging
Session Chairs: Jonathan Phillips, Google Inc. (United States) and Radka Tezaur, Intel Corporation (United States)
2:00 – 3:10 PM
Grand Peninsula D
Imaging the unseen: Taking the first picture of a black hole, Katherine Bouman, California Institute of Technology (United States)
Katherine Bouman is an assistant professor in the Computing and Mathematical Sciences Department at the California Institute of Technology. Before joining Caltech, she was a postdoctoral fellow in the Harvard-Smithsonian Center for Astrophysics. She received her PhD in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT in EECS. Before coming to MIT, she received her bachelor's degree in electrical engineering from the University of Michigan. The focus of her research is on using emerging computational methods to push the boundaries of interdisciplinary imaging.
3:10 – 3:30 PM Coffee Break
5:00 – 6:00 PM All-Conference Welcome Reception