Dates currently being confirmed; check back.

Call for Papers Announced 2 May
Journal-first (JIST/JPI) Submissions

∙ Submission site Opens 2 May 
∙ Journal-first (JIST/JPI) Submissions Due 1 Aug
∙ Final Journal-first manuscripts due 28 Oct
Conference Papers Submissions
∙ Abstract Submission Opens 1 June
∙ Priority Decision Submission Ends 15 July
∙ Extended Submission Ends  19 Sept
∙ FastTrack Conference Proceedings Manuscripts Due 25 Dec 
∙ All Outstanding Proceedings Manuscripts Due
 6 Feb 2023
Registration Opens 1 Dec
Demonstration Applications Due 19 Dec
Early Registration Ends 18 Dec

Hotel Reservation Deadline 6 Jan
Symposium begins
15 Jan

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Imaging and Multimedia Analytics at the Edge 2023

Monday 16 January 2023

KEYNOTE: Data & Learning (M1)

Session Chair: Qian Lin, HP Inc. (United States)
8:45 – 10:20 AM

Conference Welcome

KEYNOTE: Small data, big insights, Raja Bala, Amazon (United States) [view abstract]

Dr. Raja Bala is a principal applied scientist at Amazon. His research interests include computer vision, deep learning, image/video processing, mobile imaging, and color imaging. Bala is an inventor on 180 patents and has authored over 100 publications in the field of digital imaging and computer vision. He is co-editor of IEEE-Wiley book: "Computer Vision and Imaging in Intelligent Transportation Systems" and is the principal liaison for numerous industry-university partnerships. Prior to joining Amazon, Bala was principal scientist, and leader of the Collaborative Visual Computing Group at PARC. Bala is a Fellow of IS&T, and a Senior Member of IEEE.


Connecting images and AR content using CLIP embedding, Yulong Liu, Snap (United States) [view abstract]


Artificial intelligence and general data protection regulation (GDPR) – a contradiction in terms? (Invited), Reiner Fageth, CEWE Stiftung & Co.KGaA (Germany) [view abstract]


10:20 – 10:50 AM Coffee Break

Watch What You Eat (M2.1)

Session Chair: Qian Lin, HP Inc. (United States)
10:50 AM – 12:00 PM

Harnessing the power of pixels to assess dietary intake (Invited), Fengqing Zhu, Purdue University (United States) [view abstract]


Conditional synthetic food image generation, Wenjin Fu1, Yue Han2, Sriram Baireddy2, Jiangpeng He2, Mridul Gupta2, and Fengqing Zhu2; 1The Ohio State University and 2Purdue University (United States) [view abstract]


Unsupervised visual representation learning on food images, Andrew W. Peng, Jiangpeng He, and Fengqing Zhu, Purdue University (United States) [view abstract]


PANEL: Watch What You Eat: Panel on Food/Health from the Perspective of AI and Privacy (M2.2)

Panel Moderator: Reiner Fageth, CEWE Stiftung & Co.KGaA (Germany)
12:00 – 12:30 PM

12:30 – 2:00 PM Lunch

Monday 16 January PLENARY: Neural Operators for Solving PDEs

Session Chair: Robin Jenkin, NVIDIA Corporation (United States)
2:00 PM – 3:00 PM
Cyril Magnin I/II/III

Deep learning surrogate models have shown promise in modeling complex physical phenomena such as fluid flows, molecular dynamics, and material properties. However, standard neural networks assume finite-dimensional inputs and outputs, and hence, cannot withstand a change in resolution or discretization between training and testing. We introduce Fourier neural operators that can learn operators, which are mappings between infinite dimensional spaces. They are independent of the resolution or grid of training data and allow for zero-shot generalization to higher resolution evaluations. When applied to weather forecasting, neural operators capture fine-scale phenomena and have similar skill as gold-standard numerical weather models for predictions up to a week or longer, while being 4-5 orders of magnitude faster.

Anima Anandkumar, Bren professor, California Institute of Technology, and senior director of AI Research, NVIDIA Corporation (United States)


Anima Anandkumar is a Bren Professor at Caltech and Senior Director of AI Research at NVIDIA. She is passionate about designing principled AI algorithms and applying them to interdisciplinary domains. She has received several honors such as the IEEE fellowship, Alfred. P. Sloan Fellowship, NSF Career Award, and Faculty Fellowships from Microsoft, Google, Facebook, and Adobe. She is part of the World Economic Forum's Expert Network. Anandkumar received her BTech from Indian Institute of Technology Madras, her PhD from Cornell University, and did her postdoctoral research at MIT and assistant professorship at University of California Irvine.

3:00 – 3:30 PM Coffee Break

Prime Video (M3)

Session Chair: Raja Bala, Amazon (United States)
3:30 – 5:00 PM

Learn spatio-temporal downsampling for effective video upscaling (Invited), Xiaoyu Xiang1, Yapeng Tian2, Vijay Rengaranjan1, Lucas Young1, Bo Zhu1, and Rakesh Ranjan1; 1Meta and 2The University of Texas at Dallas (United States) [view abstract]


Movie character re-identification by agglomerative clustering of deep features, Samuel Ducros1,2, William Puech1, Gérard Subsol1, Mathieu Lafourcade1, Jean-Marie Barthélémy2, and Bianca Jansen van Rensburg3; 1Université de Montpellier, 2ECOSM, and 3presenter only (France) [view abstract]


Light-weight recurrent network for real-time video super-resolution, Tianqi Wang1, Qian Lin2, and Jan P. Allebach1; 1Purdue University and 2HP Labs, HP Inc. (United States) [view abstract]


Depth assisted portrait video background blurring, Yezhi Shen1, Weichen Xu1, Qian Lin2, Jan P. Allebach1, and Fengqing Zhu1; 1Purdue University and 2HP Labs, HP Inc. (United States) [view abstract]


EI 2023 Highlights Session

Session Chair: Robin Jenkin, NVIDIA Corporation (United States)
3:30 – 5:00 PM
Cyril Magnin II

Join us for a session that celebrates the breadth of what EI has to offer with short papers selected from EI conferences.

NOTE: The EI-wide "EI 2023 Highlights" session is concurrent with Monday afternoon COIMG, COLOR, IMAGE, and IQSP conference sessions.


Evaluation of image quality metrics designed for DRI tasks with automotive cameras, Valentine Klein, Yiqi LI, Claudio Greco, Laurent Chanas, and Frédéric Guichard, DXOMARK (France) [view abstract]


Human performance using stereo 3D in a helmet mounted display and association with individual stereo acuity, Bonnie Posselt, RAF Centre of Aviation Medicine (United Kingdom) [view abstract]


Smartphone-enabled point-of-care blood hemoglobin testing with color accuracy-assisted spectral learning, Sang Mok Park1, Yuhyun Ji1, Semin Kwon1, Andrew R. O’Brien2, Ying Wang2, and Young L. Kim1; 1Purdue University and 2Indiana University School of Medicine (United States) [view abstract]


Designing scenes to quantify the performance of automotive perception systems, Zhenyi Liu1, Devesh Shah2, Alireza Rahimpour2, Joyce Farrell1, and Brian Wandell1; 1Stanford University and 2Ford Motor Company (United States) [view abstract]


Visualizing and monitoring the process of injection molding, Christian A. Steinparz1, Thomas Mitterlehner2, Bernhard Praher2, Klaus Straka1,2, Holger Stitz1,3, and Marc Streit1,3; 1Johannes Kepler University, 2Moldsonics GmbH, and 3datavisyn GmbH (Austria) [view abstract]


Commissioning the James Webb Space Telescope, Joseph M. Howard, NASA Goddard Space Flight Center (United States) [view abstract]


Critical flicker frequency (CFF) at high luminance levels, Alexandre Chapiro1, Nathan Matsuda1, Maliha Ashraf2, and Rafal Mantiuk3; 1Meta (United States), 2University of Liverpool (United Kingdom), and 3University of Cambridge (United Kingdom) [view abstract]


Physics guided machine learning for image-based material decomposition of tissues from simulated breast models with calcifications, Muralikrishnan Gopalakrishnan Meena1, Amir K. Ziabari1, Singanallur Venkatakrishnan1, Isaac R. Lyngaas1, Matthew R. Norman1, Balint Joo1, Thomas L. Beck1, Charles A. Bouman2, Anuj Kapadia1, and Xiao Wang1; 1Oak Ridge National Laboratory and 2Purdue University (United States) [view abstract]


Layered view synthesis for general images, Loïc Dehan, Wiebe Van Ranst, and Patrick Vandewalle, Katholieke University Leuven (Belgium) [view abstract]


A self-powered asynchronous image sensor with independent in-pixel harvesting and sensing operations, Ruben Gomez-Merchan, Juan Antonio Leñero-Bardallo, and Ángel Rodríguez-Vázquez, University of Seville (Spain) [view abstract]


Color blindness and modern board games, Alessandro Rizzi1 and Matteo Sassi2; 1Università degli Studi di Milano and 2consultant (Italy) [view abstract]


5:00 – 6:15 PM EI 2023 All-Conference Welcome Reception (in the Cyril Magnin Foyer)

Tuesday 17 January 2023

KEYNOTE: Applications I (T1)

Session Chair: Raja Bala, Amazon (United States)
8:50 – 10:10 AM

KEYNOTE: Multi-scale representations for human pose estimation: Advances and applications, Andreas Savakis, Rochester Institute of Technology (United States) [view abstract]

Prof. Andreas Savakis is director of the Center for Human-aware AI (CHAI) and Professor of Computer Engineering at the Rochester Institute of Technology. His primary area of research is computer vision, with secondary interests in computational imaging and image processing. Savakis founded the Vision and Image Processing lab (VIP-lab) at RIT, where he works with students on topics including recognition, tracking, segmentation, pose estimation, facial expression, scene analysis, domain adaptation, and robust learning.


Robust hand hygiene monitoring for food safety using hand images, Shengtai Ju, Amy R. Reibman, and Amanda J. Deering, Purdue University (United States) [view abstract]


Evaluating the efficacy of skincare product: A realistic short-term facial pore simulation, Ling Li1, Bandara Dissanayake2, Tatsuya Omotezako2, Yunjie Zhong1, Qing Zhang3, Rizhao Cai1, Qian Zheng4, Dennis Sng1, Weisi Lin1, Yufei Wang5, and Alex C. Kot1; 1Nanyang Technological University (Singapore), 2Procter & Gamble (Singapore), 3East China Normal University (China), 4Zhejiang University (China), and 5China-Singapore International Joint Research Institute (China) [view abstract]


10:00 AM – 7:30 PM Industry Exhibition - Tuesday (in the Cyril Magnin Foyer)

10:20 – 10:50 AM Coffee Break

Applications II (T2)

Session Chair: Qian Lin, HP Inc. (United States)
10:50 AM – 12:30 PM

AI technology for aquatic and nautical search and rescue (TANSAR), Theus Aspiras, Ruixu Liu, and Vijayan K. Asari, University of Dayton (United States) [view abstract]


Wearable spectrum imaging and telemetry at edge, Yang Cai, CMU (United States) [view abstract]


Eidetic recognition of cattle using keypoint alignment, Manu Ramesh, Amy R. Reibman, and Jacquelyn Boerman, Purdue University (United States) [view abstract]


Challenges and constraints when applying few shot learning to a real-world scenario: In-the-wild camera-trap species classification, Haoyu Chen, Stacy Lindshield, and Amy R. Reibman, Purdue University (United States) [view abstract]


Smartphone-enabled point-of-care blood hemoglobin testing with color accuracy-assisted spectral learning, Sang Mok Park1, Yuhyun Ji1, Semin Kwon1, Andrew R. O’Brien2, Ying Wang2, and Young L. Kim1; 1Purdue University and 2Indiana University School of Medicine (United States) [view abstract]


12:30 – 2:00 PM Lunch

Tuesday 17 January PLENARY: Embedded Gain Maps for Adaptive Display of High Dynamic Range Images

Session Chair: Robin Jenkin, NVIDIA Corporation (United States)
2:00 PM – 3:00 PM
Cyril Magnin I/II/III

Images optimized for High Dynamic Range (HDR) displays have brighter highlights and more detailed shadows, resulting in an increased sense of realism and greater impact. However, a major issue with HDR content is the lack of consistency in appearance across different devices and viewing environments. There are several reasons, including varying capabilities of HDR displays and the different tone mapping methods implemented across software and platforms. Consequently, HDR content authors can neither control nor predict how their images will appear in other apps.

We present a flexible system that provides consistent and adaptive display of HDR images. Conceptually, the method combines both SDR and HDR renditions within a single image and interpolates between the two dynamically at display time. We compute a Gain Map that represents the difference between the two renditions. In the file, we store a Base rendition (either SDR or HDR), the Gain Map, and some associated metadata. At display time, we combine the Base image with a scaled version of the Gain Map, where the scale factor depends on the image metadata, the HDR capacity of the display, and the viewing environment.

Eric Chan, Fellow, Adobe Inc. (United States)


Eric Chan is a Fellow at Adobe, where he develops software for editing photographs. Current projects include Photoshop, Lightroom, Camera Raw, and Digital Negative (DNG). When not writing software, Chan enjoys spending time at his other keyboard, the piano. He is an enthusiastic nature photographer and often combines his photo activities with travel and hiking.

Paul M. Hubel, director of Image Quality in Software Engineering, Apple Inc. (United States)


Paul M. Hubel is director of Image Quality in Software Engineering at Apple. He has worked on computational photography and image quality of photographic systems for many years on all aspects of the imaging chain, particularly for iPhone. He trained in optical engineering at University of Rochester, Oxford University, and MIT, and has more than 50 patents on color imaging and camera technology. Hubel is active on the ISO-TC42 committee Digital Photography, where this work is under discussion, and is currently a VP on the IS&T Board. Outside work he enjoys photography, travel, cycling, coffee roasting, and plays trumpet in several bay area ensembles.

3:00 – 3:30 PM Coffee Break

5:30 – 7:00 PM EI 2023 Symposium Demonstration Session (in the Cyril Magnin Foyer)

Wednesday 18 January 2023

10:00 AM – 3:30 PM Industry Exhibition - Wednesday (in the Cyril Magnin Foyer)

10:20 – 10:50 AM Coffee Break

12:30 – 2:00 PM Lunch

Wednesday 18 January PLENARY: Bringing Vision Science to Electronic Imaging: The Pyramid of Visibility

Session Chair: Andreas Savakis, Rochester Institute of Technology (United States)
2:00 PM – 3:00 PM
Cyril Magnin I/II/III

Electronic imaging depends fundamentally on the capabilities and limitations of human vision. The challenge for the vision scientist is to describe these limitations to the engineer in a comprehensive, computable, and elegant formulation. Primary among these limitations are visibility of variations in light intensity over space and time, of variations in color over space and time, and of all of these patterns with position in the visual field. Lastly, we must describe how all these sensitivities vary with adapting light level. We have recently developed a structural description of human visual sensitivity that we call the Pyramid of Visibility, that accomplishes this synthesis. This talk shows how this structure accommodates all the dimensions described above, and how it can be used to solve a wide variety of problems in display engineering.

Andrew B. Watson, chief vision scientist, Apple Inc. (United States)


Andrew Watson is Chief Vision Scientist at Apple, where he leads the application of vision science to technologies, applications, and displays. His research focuses on computational models of early vision. He is the author of more than 100 scientific papers and 8 patents. He has 21,180 citations and an h-index of 63. Watson founded the Journal of Vision, and served as editor-in-chief 2001-2013 and 2018-2022. Watson has received numerous awards including the Presidential Rank Award from the President of the United States.

3:00 – 3:30 PM Coffee Break

Imaging and Multimedia Analytics at the Edge 2023 Interactive (Poster) Paper Session

5:30 – 7:00 PM
Cyril Magnin Foyer

The following works will be presented at the EI 2023 Symposium Interactive (Poster) Paper Session.

Lightweight single pass numerical reading extraction for displays in the wild, Yan-Ming Chiou and Bob Price, Palo Alto Research Center Incorporated (United States) [view abstract]


Robust tracking of industrial objects across environments from small samples in single environments using chroma-key and occlusion augmentations, Yan-Ming Chiou and Bob Price, Palo Alto Research Center Incorporated (United States) [view abstract]


5:30 – 7:00 PM EI 2023 Symposium Interactive (Poster) Paper Session (in the Cyril Magnin Foyer)

5:30 – 7:00 PM EI 2023 Meet the Future: A Showcase of Student and Young Professionals Research (in the Cyril Magnin Foyer)

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