Monday January 27, 2020
Plug and Play Approaches
Session Chair:
W. Clem Karl, Boston University (United States)
8:45 – 10:10 AM
Grand Peninsula B/C
8:45
Conference Welcome
8:50COIMG-005
Plug-and-play AMP for image recovery with Fourier-structured operators, Subrata Sarkar, Rizwan Ahmad, and Philip Schniter, Ohio State University (United States)
9:10COIMG-006
A splitting-based iterative algorithm for GPU-accelerated statistical dual-energy x-ray CT reconstruction, Fangda Li, Ankit Manerikar, Tanmay Prakash, and Avinash Kak, Purdue University (United States)
9:30COIMG-007
Proximal Newton Methods for x-ray imaging with non-smooth regularization, Tao Ge, Umberto Villa, Ulugbek Kamilov, and Joseph O’Sullivan, Washington University in St. Louis (United States)
9:50COIMG-008
Integrating learned data and image models through consensus equilibrium, W. Clem Karl and Muhammad Usman Ghani, Boston University (United States)
10:10 – 10:50 AM Coffee Break
Scientific Imaging I
Session Chair:
Eric Miller, Tufts University (United States)
10:50 AM – 12:30 PM
Grand Peninsula B/C
10:50COIMG-043
Learned priors for the joint ptycho-tomography reconstruction, Selin Aslan, Argonne National Laboratory (United States)
11:10COIMG-044
A joint reconstruction and lambda tomography regularization technique for energy-resolved x-ray imaging, James Webber, Eric Quinto, and Eric Miller, Tufts University (United States)
11:30COIMG-045
Generalized tensor learning with applications to 4D-STEM image denoising, Rungang Han1, Rebecca Willett2, and Anru Zhang1; 1University of Wisconsin-Madison and 2University of Chicago (United States)
11:50COIMG-046
Computational imaging in infrared sensing of the atmosphere, Adam Milstein, Yaron Rachlin, Corrie Smeaton, Charles Wynn, Ryan Sullenberger, Philip Chapnik, Steven Leman, and William Blackwell, MIT Lincoln Laboratory (United States)
12:10COIMG-047
Learning optimal sampling for computational imaging, He Sun1, Adrian Dalca2, and Katherine Bouman1; 1California Institute of Technology and 2Harvard Medical School (United States)
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
Scientific Imaging II
Session Chair:
Brendt Wohlberg, Los Alamos National Laboratory (United States)
3:30 – 4:10 PM
Grand Peninsula B/C
3:30COIMG-058
Revealing subcellular structures with live-cell and 3D fluorescence nanoscopy, Fang Huang, Purdue University (United States)
3:50COIMG-059
Single-shot coded diffraction system for 3D object shape estimation, Samuel Pinilla1, Laura Galvis1, Karen Egiazarian2, and Henry Arguello1; 1Universidad Industrial de Santander (Colombia) and 2Tampere University (Finland)
PANEL: The Future of Computational Imaging
Panel Moderator: Charles Bouman, Purdue University (United States)
Panelists: Katherine Bouman, California Institute of Technology (United States); Sergio Goma, Qualcomm Inc. (United States); Peyman Milanfar, Google Research (United States); Casey Pellizzari, United States Air Force Academy (United States); and Brendt Wohlberg, Los Alamos National Laboratory (United States)
4:10 – 4:50 PM
Grand Peninsula B/C
Electronic imaging is evolving rapidly under the influence of new imaging devices combined with computational approaches and artificial intelligence. Computational imaging, composing images through a combination of data acquisition and data processing, has applications to autonomous vehicles, medical imaging, astronomical imaging, remote sensing, etc. Computational imaging topics surface throughout the EI 2020 week, including the Monday plenary, "Imaging the Unseen: Taking the First Picture of a Black Hole," and presentations in conferences such as Autonomous Vehicles and Machines 2020, Computational Imaging XVIII, Imaging and Multimedia Analytics in a Web and Mobile World 2020, and Image Processing: Algorithms and Systems XVIII. This panel brings together researchers and practitioners to look into the futures of these technologies.
5:00 – 6:00 PM All-Conference Welcome Reception
Tuesday January 28, 2020
7:30 – 8:45 AM Women in Electronic Imaging Breakfast (pre-registration required)
KEYNOTE: Computation and Photography
Session Chair: Charles Bouman, Purdue University (United States)
8:50 – 9:30 AM
Grand Peninsula B/C
COIMG-089
Computation and photography: How the mobile phone became a camera, Peyman Milanfar, Google Research (United States)
Peyman Milanfar is a principal scientist / director at Google Research, where he leads Computational Imaging. Previously, he was professor of electrical engineering at UC Santa Cruz (1999-2014). Most recently, Peyman's team at Google developed the "Super Res Zoom" pipeline for the Pixel phones. Peyman received his BS in electrical engineering and mathematics from UC Berkeley, and his MS and PhD in EECS from MIT. He founded MotionDSP, which was acquired by Cubic Inc. He is a Distinguished Lecturer of the IEEE Signal Processing Society, and a Fellow of the IEEE.
Optically-Coherent and Interferometric Imaging I
Session Chair:
Casey Pellizzari, United States Air Force Academy (United States)
9:30 – 10:30 AM
Grand Peninsula B/C
Optically-coherent and interferometric imaging sensors provide a means to measure both the amplitude and phase of incoming light. These sensors depend on computational-based methods to convert real-valued intensity measurements into amplitude and phase information for image reconstruction. Additionally, computational methods have helped overcome many of the practical issues associated with these sensors as well as enabled new imaging modalities. This session explores the coupling between optically-coherent and interferometric sensors and the computational methods that enable and extend their use. Example topic areas include both coherent and incoherent holography, coherent lidar, microscopy, metrology, and astronomy.
9:30COIMG-111
Spectral shearing LADAR, Jason Stafford1, David Rabb1, Kyle Watson2, Brett Spivey2, and Ryan Galloway3; 1United States Air Force Research Laboratory, 2JASR Systems, and 3Montana State University (United States)
9:50COIMG-112
3D computational phase microscopy with multiple-scattering samples, Laura Waller1, Shwetadwip Chowdhury1, Michael Chen1, Yonghuan David Ren1, Regina Eckert1, Michael Kellman1, and Eemrah Bostan2; 1University of California, Berkeley (United States) and 2University of Amsterdam (the Netherlands)
10:10COIMG-113
Imaging through deep turbulence and emerging solutions, Mark Spencer1, Casey Pellizzari2, and Charles Bouman3; 1Air Force Research Laboratory, 2United States Air Force Academy, and 3Purdue University (United States)
10:00 AM – 7:30 PM Industry Exhibition - Tuesday
10:10 – 10:50 AM Coffee Break
Optically-Coherent and Interferometric Imaging II
Session Chair:
Casey Pellizzari, United States Air Force Academy (United States)
10:50 – 11:30 AM
Grand Peninsula B/C
Optically-coherent and interferometric imaging sensors provide a means to measure both the amplitude and phase of incoming light. These sensors depend on computational-based methods to convert real-valued intensity measurements into amplitude and phase information for image reconstruction. Additionally, computational methods have helped overcome many of the practical issues associated with these sensors as well as enabled new imaging modalities. This session explores the coupling between optically-coherent and interferometric sensors and the computational methods that enable and extend their use. Example topic areas include both coherent and incoherent holography, coherent lidar, microscopy, metrology, and astronomy.
10:50COIMG-125
Holographic imaging through highly attenuating fog conditions, Abbie Watnik1, Samuel Park1, James Lindle2, and Paul Lebow3; 1United States Naval Research Laboratory, 2DCS Corporation, and 3Alaire Technologies (United States)
11:10COIMG-126
Intensity interferometry-based 3D ranging, Fabian Wagner1, Florian Schiffers1, Florian Willomitzer1, Oliver Cossairt1, and Andreas Velten2; 1Northwestern University and 2University of Wisconsin-Madison (United States)
Phase Coherent Imaging
Session Chair:
Charles Bouman, Purdue University (United States)
11:30 AM – 12:10 PM
Grand Peninsula B/C
11:30COIMG-146
Constrained phase retrieval using a non-linear forward model for x-ray phase contrast tomography, K. Aditya Mohan, Jean-Baptiste Forien, and Jefferson Cuadra, Lawrence Livermore National Laboratory (United States)
11:50COIMG-147
Multi-wavelength remote digital holography: Seeing the unseen by imaging off scattering surfaces and imaging through scattering media, Florian Willomitzer1, Prasanna Rangarajan2, Fengqiang Li1, Muralidhar Madabhushi Balaji2, and Oliver Cossairt1; 1Northwestern University and 2Southern Methodist University (United States)
Recent Progress in Computational Microscopy I
Session Chair:
Singanallur Venkatakrishnan, Oak Ridge National Laboratory (United States)
12:10 – 12:30 PM
Grand Peninsula B/C
Microscopy is currently experiencing an exciting era of new methodological developments with computation at its core. The recent progress in compressive imaging, numerical physical models, regularization techniques, large-scale optimization methods, and machine learning are leading to a faster, quantitative, and reliable microscopic imaging. Though many computational methods are being developed independently for different modalities, their combination may be seen as example of a new paradigm of rapid, comprehensive, and information-rich computational microscopy. This session will explore cross-cutting themes in several modalities such as optical, neutron, x-ray, and electron microscopy and will attempt to promote transfer of ideas between investigators in these different areas.
12:10COIMG-152
3D DiffuserCam: Computational microscopy with a lensless imager, Laura Waller, University of California, Berkeley (United States)
12:30 – 2:00 PM Lunch
PLENARY: Automotive 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 in the autonomous vehicle revolution, Gary Hicok, NVIDIA Corporation (United States)
Gary Hicok is senior vice president of hardware development at NVIDIA, and is responsible for Tegra System Engineering, which oversees Shield, Jetson, and DRIVE platforms. Prior to this role, Hicok served as senior vice president of NVIDIA’s Mobile Business Unit. This vertical focused on NVIDIA’s Tegra mobile processor, which was used to power next-generation mobile devices as well as in-car safety and infotainment systems. Before that, Hicok ran NVIDIA’s Core Logic (MCP) Business Unit also as senior vice president. Throughout his tenure with NVIDIA, Hicok has also held a variety of management roles since joining the company in 1999, with responsibilities focused on console gaming and chipset engineering. He holds a BSEE from Arizona State University and has authored 33 issued patents.
3:10 – 3:30 PM Coffee Break
Recent Progress in Computational Microscopy II
Session Chair:
Singanallur Venkatakrishnan, Oak Ridge National Laboratory (United States)
3:30 – 5:10 PM
Grand Peninsula B/C
Microscopy is currently experiencing an exciting era of new methodological developments with computation at its core. The recent progress in compressive imaging, numerical physical models, regularization techniques, large-scale optimization methods, and machine learning are leading to a faster, quantitative, and reliable microscopic imaging. Though many computational methods are being developed independently for different modalities, their combination may be seen as example of a new paradigm of rapid, comprehensive, and information-rich computational microscopy. This session will explore cross-cutting themes in several modalities such as optical, neutron, x-ray, and electron microscopy and will attempt to promote transfer of ideas between investigators in these different areas.
3:30COIMG-156
Computational nanoscale imaging with synchrotron radiation, Doga Gursoy, Argonne National Laboratory (United States)
3:50COIMG-157
Recent advances in 3D structured illumination microscopy with reduced data-acquisition, Chrysanthe Preza, The University of Memphis (United States)
4:10COIMG-158
Method of moments for single-particle cryo-electron microscopy, Amit Singer, Princeton University (United States)
4:30COIMG-159
Computational imaging in transmission electron microscopy: Atomic electron tomography and phase contrast imaging, Colin Ophus, Lawrence Berkeley National Laboratory (United States)
4:50COIMG-160
3D and 4D computational imaging of molecular orientation with multiview polarized fluorescence microscopy, Talon Chandler1, Min Guo2, Rudolf Oldenbourg3, Hari Shroff2, and Patrick La Riviere1; 1The University of Chicago, 2National Institutes of Health, and 3Marine Biological Laboratory (United States)
DISCUSSION: Tuesday Tech Mixer
Hosts:
Charles Bouman, Purdue University (United States); Gregery Buzzard, Purdue University (United States); and Robert Stevenson, University of Notre Dame (United States)
5:10 – 5:40 PM
Grand Peninsula B/C
Computational Imaging Conference Tuesday wrap-up discussion and refreshments.
5:30 – 7:30 PM Symposium Demonstration Session
Wednesday January 29, 2020
Medical Imaging
Session Chair:
Evan Morris, Yale University (United States)
8:50 – 10:10 AM
Grand Peninsula B/C
8:50COIMG-191
Model comparison metrics require adaptive correction if parameters are discretized: Application to a transient neurotransmitter signal in PET data, Heather Liu and Evan Morris, Yale University (United States)
9:10COIMG-192
Computational pipeline and optimization for automatic multimodal reconstruction of marmoset brain histology, Brian Lee1, Meng Lin2, Junichi Hata2, Partha Mitra3, and Michael Miller1; 1Johns Hopkins University (United States), 2RIKEN Brain Science Institute (Japan), and 3Cold Spring Harbor Laboratory (United States)
9:30COIMG-193
Model-based approach to more accurate stopping power ratio estimation for proton therapy, Maria Medrano1, Jeffrey Williamson2, Bruce Whiting3, David Politte4, Shuanyue Zhang1, Tyler Webb1, Tianyu Zhao4, Ruirui Liu4, Mariela Porras-Chaverri2, Tao Ge1, Rui Liao1, and Joseph O’Sullivan1; 1Washington University in St. Louis (United States), 2University of Costa Rica (Costa Rica), 3University of Pittsburg (United States), and 4Washington University School of Medicine (United States)
9:50COIMG-194
Deep learning based regularized image reconstruction for respiratory gated PET, Tiantian Li1, Mengxi Zhang1, Wenyuan Qi2, Evren Asma2, and Jinyi Qi1; 1University of California, Davis and 2Canon Medical Research (United States), Inc. (United States)
10:00 AM – 3:30 PM Industry Exhibition - Wednesday
10:10 – 10:50 AM Coffee Break
Computational Imaging Applications to Materials Characterization
Session Chair:
Jeffrey Simmons, Air Force Research Laboratory (United States)
10:50 AM – 12:30 PM
Grand Peninsula B/C
Materials science, like physics, focuses on forward modeling almost exclusively for analysis. This creates opportunities for imaging scientists to make significant advances by introducing modern, inversion-based methods for analysis of microscope imagery. Materials Science emerged as a true ``scientific'' discipline, with the development of microscopy because it allowed the materials scientist to observe the ``microstructure,'' that is, the texture produced by the processes used for preparing the material. For this reason, materials science and microscopy have always been intimately linked, with the major connection being microstructure as a means of controlling properties. Until quite recently materials characterization was largely ``photons-on-film.'' With the digital transition of microscopy from film to data file, microscopy became a computational imaging problem. With the automation of data collection, it became imperative to develop algorithms requiring less human interaction. This session highlights recent advances in materials science as a direct consequence of cross-disciplinary approaches between computational imaging and materials science. This session covers, but is not limited to, forward modeling of material-probe-detector interactions, segmentation, anomaly detection, data fusion, denoising, learning approaches, detection and tracking, and super-resolution.
10:50COIMG-404
Deepfake, artificial intelligence: will machines replace us all?, Huolin Xin, University of California, Irvine (United States)
11:10COIMG-248
Crystallographic symmetry for data augmentation in detecting dendrite cores, Lan Fu1, Hongkai Yu2, Megna Shah3, Jeffrey Simmons3, and Song Wang1; 1University of South Carolina, 2University of Texas, and 3Air Force Research Laboratory (United States)
11:30COIMG-249
Multi-resolution data fusion for super resolution imaging of biological materials, Emma Reid1, Cheri Hampton2, Asif Mehmood2, Gregery Buzzard1, Lawrence Drummy2, and Charles Bouman1; 1Purdue University and 2Air Force Research Laboratory (United States)
11:50COIMG-250
Void detection and fiber extraction for statistical characterization of fiber-reinforced polymers, Camilo Aguilar Herrera and Mary Comer, Purdue University (United States)
12:10COIMG-251
Applications of denoising, structure optimization, and deep learning in high resolution electron microscopy, Chenyu Zhang and Paul Voyles, University of Wisconsin-Madison (United States)
12:30 – 2:00 PM Lunch
PLENARY: VR/AR Future Technology
Session Chairs: Jonathan Phillips, Google Inc. (United States) and Radka Tezaur, Intel Corporation (United States)
2:00 – 3:10 PM
Grand Peninsula D
Quality screen time: Leveraging computational displays for spatial computing, Douglas Lanman, Facebook Reality Labs (United States)
Douglas Lanman is the director of Display Systems Research at Facebook Reality Labs, where he leads investigations into advanced display and imaging technologies for augmented and virtual reality. His prior research has focused on head-mounted displays, glasses-free 3D displays, light-field cameras, and active illumination for 3D reconstruction and interaction. He received a BS in Applied Physics with Honors from Caltech in 2002 and his MS and PhD in Electrical Engineering from Brown University in 2006 and 2010, respectively. He was a senior research scientist at NVIDIA Research from 2012 to 2014, a postdoctoral associate at the MIT Media Lab from 2010 to 2012, and an assistant research staff member at MIT Lincoln Laboratory from 2002 to 2005. His most recent work has focused on developing the Oculus Half Dome: an eye-tracked, wide-field-of-view varifocal HMD with AI-driven rendering.
3:10 – 3:30 PM Coffee Break
Materials Imaging
Session Chair:
David Castañón, Boston University (United States)
3:30 – 4:10 PM
Grand Peninsula B/C
3:30COIMG-263
Mueller matrix imaging for classifying similar diffuse materials, Lisa Li, Meredith Kupinski, Madellyn Brown, and Russell Chipman, The University of Arizona (United States)
3:50COIMG-264
Modeling multivariate tail behavior in materials data, Lucas Costa, Tomas Comer, Daniel Greiwe, Camilo Aguilar Herrera, and Mary Comer, Purdue University (United States)
Security Imaging
Session Chair:
David Castañón, Boston University (United States)
4:10 – 4:50 PM
Grand Peninsula B/C
4:10COIMG-293
A spectrum-adaptive decomposition method for effective atomic number estimation using dual energy CT, Ankit Manerikar, Fangda Li, Tanmay Prakash, and Avinash Kak, Purdue University (United States)
4:30COIMG-294
Metal artifact reduction in dual-energy CT with synthesized monochromatic basis for baggage screening, Sandamali Devadithya and David Castañón, Boston University (United States)
DISCUSSION: Wednesday Tech Mixer
Hosts:
Charles Bouman, Purdue University (United States); Gregery Buzzard, Purdue University (United States); and Robert Stevenson, University of Notre Dame (United States)
4:50 – 5:30 PM
Grand Peninsula B/C
Computational Imaging Conference Wednesday wrap-up discussion and refreshments.
Computational Imaging XVIII Interactive Posters Session
5:30 – 7:00 PM
Sequoia
The following works will be presented at the EI 2020 Symposium Interactive Posters Session.
COIMG-305
Connected-tube MPP model for unsupervised 3D fiber detection, Tianyu Li, Mary Comer, and Michael Sangid, Purdue University (United States)
COIMG-306
Imaging through scattering media with a learning based prior, Florian Schiffers, Lionel Fiske, Pablo Ruiz, Aggelos K Katsaggelos, and Oliver Cossairt, Northwestern University (United States)
COIMG-307
Reconstruction of 2D seismic wavefields from nonuniformly sampled sources, Laura Galvis1, Juan Ramirez1, Edwin Vargas1, Ofelia Villarreal2, William Agudelo3, and Henry Arguello1; 1Universidad Industrial de Santander, 2Cooperativa de Tecnólogos e Ingenieros de la Industria del Petróleo y Afines, TIP, and 3Instituto Colombiano del Petróleo, ICP, Ecopetrol S.A. (Colombia)
5:30 – 7:00 PM EI 2020 Symposium Interactive Posters Session
5:30 – 7:00 PM Meet the Future: A Showcase of Student and Young Professionals Research
Thursday January 30, 2020
Deep Learning in Computational Imaging
Session Chair:
Gregery Buzzard, Purdue University (United States)
8:50 – 10:10 AM
Grand Peninsula B/C
8:50COIMG-341
2D label free microscopy imaging analysis using machine learning, Han Hu1, Yang Lei2, Daisy Xin2, Viktor Shkolnikov2, Steven Barcelo2, Jan Allebach1, and Edward Delp1; 1Purdue University and 2HP Labs, HP Inc. (United States)
9:10COIMG-342
ProPaCoL-Net: A novel recursive stereo SR net with progressive parallax coherency learning, Jeonghun Kim and Munchurl Kim, Korea Advanced Institute of Science and Technology (Republic of Korea)
9:30COIMG-343
Deep learning method for height estimation of sorghum in the field using LiDAR, Matthew Waliman and Avideh Zakhor, University of California, Berkeley (United States)
9:50COIMG-344
Background subtraction in diffraction x-ray images using deep CNN, Rodrigo Aranguren Carmona, Gady Agam, and Thomas Irving, Illinois Institute of Technology (United States)
10:10 – 10:50 AM Coffee Break
Algorithm/Hardware Co-Design for Computational Imaging
Session Chair:
Sergio Goma, Qualcomm Inc. (United States)
10:50 AM – 12:10 PM
Grand Peninsula B/C
The aim of this session is to take computational imaging concepts a step further and to set a stepping stone towards an optimal, technology dependent implementation of computational imaging: algorithm-hardware co-design. Complex algorithms thrive on clean data sets therefore sensors that are designed in conjunction with supporting algorithms can offer significantly improved results. This session is soliciting original contributions that relate to the joint design of sensors and/or technology in conjunction with algorithms.
10:50COIMG-355
Estimation of the background illumination in optical reflectance microscopy, Charles Brookshire1, Michael Uchic2, Victoria Kramb1, Tyler Lesthaeghe3, and Keigo Hirakawa1; 1University of Dayton, 2Air Force Research Laboratory, and 3University of Dayton Research Institute (United States)
11:10COIMG-357
Skin chromophore estimation from mobile selfie images using constrained independent component analysis, Raja Bala1, Luisa Polania2, Ankur Purwar3, Paul Matts4, and Martin Maltz5; 1Palo Alto Research Center (United States), 2Target Corporation (United States), 3Procter & Gamble (Singapore), 4Procter & Gamble (United Kingdom), and 5Xerox Corporation (United States)
11:30COIMG-358
Computational imaging: Algorithm/hardware co-design considerations, Sergio Goma, Qualcomm Inc. (United States)
11:50COIMG-359
Statistical inversion methods in mobile imaging, Hasib Siddiqui, Qualcomm Technologies Inc. (United States)
12:30 – 2:00 PM Lunch
Computer Vision I
Session Chair:
Robert Stevenson, University of Notre Dame (United States)
2:00 – 3:00 PM
Grand Peninsula B/C
2:00COIMG-377
Efficient multilevel architecture for depth estimation from a single image, Nilesh Pandey, Bruno Artacho, and Andreas Savakis, Rochester Institute of Technology (United States)
2:20COIMG-378
Sky segmentation for enhanced depth reconstruction and Bokeh rendering with efficient architectures, Tyler Nuanes1,2, Matt Elsey2, Radek Grzeszczuk2, and John Shen1; 1Carnegie Mellon University and 2Light (United States)
2:40COIMG-379
A dataset for deep image deblurring aided by inertial sensor data, Shuang Zhang, Ada Zhen, and Robert Stevenson, University of Notre Dame (United States)
3:00 – 3:30 PM Coffee Break
Computer Vision II
Session Chair:
Robert Stevenson, University of Notre Dame (United States)
3:30 – 4:30 PM
Grand Peninsula B/C
3:30COIMG-390
On the distinction between phase images and two-view light field for PDAF of mobile imaging, Chi-Jui (Jerry) Ho and Homer Chen, National Taiwan University (Taiwan)
3:50COIMG-391
Indoor layout estimation by 2D LiDAR and camera fusion, Jieyu Li and Robert Stevenson, University of Notre Dame (United States)
4:10COIMG-392
Senscape: Modeling and presentation of uncertainty in fused sensor data live image streams, Henry Dietz and Paul Eberhart, University of Kentucky (United States)