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  28 January - 2 February, 2018 • Burlingame, California USA

Preliminary Program

Imaging and Multimedia Analytics in a Web and Mobile World 2018

Conference Keywords:  Multimedia Analysis, Machine Learning, Mobile, Imaging, Web

Learn more—Conference At-a-Glance and List of Short Course associated with IMAWM topics:
Conference Flyer

Wednesday January 31, 2018

Keynote: Deep Learning for Recognition and Detection I

Session Chair: Qian Lin, HP Labs, HP Inc. (United States)
9:10 – 10:10 AM
Harbour A-B

How does building a low cost vision sensor teach us about deep learning?, Tianli Yu, Morpx Inc. (United States)

Dr. Tianli Yu is the CEO and co-founder of Morpx Inc., a startup based in Hangzhou that delivers innovative computer vision hardware and software. He received his PhD in ECE from the University of Illinois at Urbana Champaign (2006). After graduation, he's been a senior computer vision researcher in Motorola Labs working on the embedded stereo depth camera for Motorola's phones. Later, Dr. Yu joined like.com and designed algorithms to assist shoppers in finding their personal styles. Like.com was eventually acquired by Google in 2010. After working for a few years in the design of large scale visual search and recognition algorithms for Google Shopping, Dr. Yu founded Morpx with his friend Frank Ran in late 2013. Morpx is the second time in his career that he is working to build an ultra-compact and super energy efficient computer vision system.

Deep Learning has been proven to be very successful for many recognition problems in computer vision, but the reason for this success is still relatively unclear, largely due to its enormous computation and non-linearity hiding behind the seemingly simple stacked neural layers. These complexities also create practical problems for embedded applications where power and computation resources are extremely limited. Morpx Inc has been spending years on delivering low-cost / low-complexity visual recognition system. We believe that there are still large computational redundancies in the commonly used deep learning networks. In our lab, by scaling down the deep networks to bare minimum and test how different optimization techniques affect these networks’ performance, we gained some useful insights that cannot be observed on regular deep nets. In this talk, I will present some of these insights and a survey of many others from the global embedded vision community. We hope that these insights will shed some lights on the directions where a convincing theory for deep learning could later be developed.

10:00 AM – 4:00 PM Industry Exhibit

10:10 – 10:50 AM Coffee Break

Deep Learning for Recognition and Detection II

Session Chairs: Andreas Savakis, Rochester Institute of Technology (United States) and Jane You, The Hong Kong Polytechnic University (Hong Kong)
10:50 AM – 12:30 PM
Harbour A-B

Depth and super-pixel extraction for augmenting human detection (Invited), Theus Aspiras, Hussin Ragb, and Vijayan Asari, University of Dayton (United States)

Vision based vehicle re-identification by fusion of multiple features, Geng Yang1, Jane You2, Zhenhua Guo3, and Qin Li1; 1Shenzhen Genvict Technologies Co., Ltd. (China), 2The Hong Kong Polytechnic University (Hong Kong), and 3Tsinghua University Shenzhen Graduate School (China)

Hierarchical Auto-associative Polynomial Convolutional Neural Network (HAP-CNN) for pattern classification, Patrick Martell, University of Dayton Research Institute (United States)

Learn a hybrid collaborative representation for fine-grained image classification, Wenyang Xie1, Bao-Di Liu1, Xue Li2, and Yan-Jiang Wang1; 1University of China University of Petroleum (Huadong) and 2Tsinghua University (China)

12:30 – 2:00 PM Lunch

2:00 – 3:00 PM PLENARY: Ubiquitous, Consumer AR Systems to Supplant Smartphones

3:00 – 3:30 PM Coffee Break

Deep Learning for Face Recognition

Session Chair: Reiner Fageth, CEWE Stiftung & Co. KGAA (Germany)
3:30 – 5:10 PM
Harbour A-B

One-shot face recognition: A review (Invited), Yandong Guo and Lei Zhang, Microsoft Research (United States)

Face liveness detection based on joint analysis of RGB and near-infrared image of faces, Lingxue Song and Changsong Liu, Tsinghua University (China)

CNN based facial landmark detection, Ruiyi Mao1, Qian Lin2, and Jan Allebach1; 1Purdue University and 2HP Labs, HP Inc. (United States)

Empirical study of image compression for palm vein recognition, Zhenhua Guo1, Qin Li2, Yujiu Yang1, and Jane You3; 1Tsinghua University (China), 2Shenzhen Institute & Information Techology (China), and 3The Hong Kong Polytechnic University (Hong Kong)

5:30 – 7:00 PM EI 2018 Symposium Interactive Papers (Poster) Session

5:30 – 7:00 PM Meet the Future: A Showcase of Student and Young Professionals Research

Thursday February 1, 2018

Deep Learning for Recognition and Detection III

Session Chair: Zhigang Fan, Apple Inc. (United States)
9:10 – 10:10 AM
Harbour A-B

3D Shape Retrieval using volumetric and image convolutional neural networks: A meta-algorithmic approach, Ruiting Shao1, Yang Lei2, Jian Fan2, and Jerry Liu2; 1Purdue University and 2HP Inc. (United States)

A new fast template matching algorithm for object detection, Jichao Jiao1, Weihua Tang2, Xin Wang1, and Zhongliang Deng1; 1Beijing University of Posts and Telecommunications and 2China State Construction Engineering Corporation (China)

A feature fusion strategy for human detection in omnidirectional camera imagery, Hussin Ragb and Vijayan Asari, University of Dayton (United States)

10:10 – 10:50 AM Coffee Break

Multimedia Analytics in Online Systems

Session Chair: Vijayan Asari, University of Dayton (United States)
10:50 AM – 12:30 PM
Harbour A-B

Has mobile photography changed the users’ behavior while ordering printed products? (Invited), Reiner Fageth, CEWE Stiftung & Co. KGAA (Germany)

Application of natural language processing to an online fashion marketplace, Kendal Norman1, Zhi Li1, Young-Taek Oh1, Gautam Golwala2, Sathya Sundaram2, and Jan Allebach1; 1Purdue University and 2Poshmark Inc. (United States)

Multimedia analytics platform for profiling keywords embedded in photo catalogues, Emiliano Pallotti, Federica Mangiatordi, Andrea Bernardini, and Licia Capodiferro, Fondazione Ugo Bordoni (Italy)

Use of color information in the analysis of fashion photographs, Zhi Li1, Gautam Golwala2, Sathya Sundaram2, and Jan Allebach1; 1Purdue University and 2Poshmark Inc. (United States)

12:30 – 2:00 PM Lunch

Mobile Image Analytics and Augmented Reality

Session Chair: Yandong Guo, Microsoft Research (United States)
2:00 – 3:20 PM
Harbour A-B

Semantic pose machines (Invited), Ying-Kai Huang and Andreas Savakis, Rochester Institute of Technology (United States)

Learning enhancement with mobile augmented reality, Xunyu Pan and Joseph Shipway, Frostburg State University (United States)

Person segmentation using convolutional neural networks with dilated convolutions, David Ho1 and Qian Lin2; 1Purdue University and 2HP Labs, HP Inc. (United States)

3:20 – 3:50 PM Coffee Break

Multi-Media Object Detection

Session Chair: Jan Allebach, Purdue University (United States)
3:50 – 4:50 PM
Harbour A-B

Deep learning for moving object detection from a single camera in UAVs (Invited), Dong Hye Ye, Qiulin Chen, Jing Li, Juan Wachs, and Charles Bouman, Purdue University (United States)

Logo detection and recognition with synthetic images, Daniel Mas Montserrat1, Qian Lin2, Jan Allebach1, and Edward Delp1; 1Purdue University and 2HP Labs, HP Inc. (United States)

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Important Dates
Call for Papers Announced 1 Mar 2017
Review Abstracts Due (refer to For Authors page)
· Regular Submission Ends 15 Aug 2017
· Late Submission Ends  10 Sept 2017
Registration Opens
Now Open
Hotel Reservation Deadline
12 Jan 2018
Early Registration Ends 8 Jan 2018
Conference Starts 28 Jan 2018 

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View 2017 Proceedings
View 2016 Proceedings

Conference Chairs
Jan Allebach, Purdue University (United States); Zhigang Fan, Apple Inc. (United States); Qian Lin, HP Inc. (United States)

Program Committee
Gady Agam, Illinois Institute of Technology (United States); Vijayan Asari, University of Dayton (United States); Reiner Fageth, CEWE Stiftung & Co. KGaA (Germany); Yi Fang, New York University Abu Dhabi (United States); Michael Gormish, Ricoh Innovations, Inc. (United States); Yandong Guo, Microsoft Corporation (United States); Ali Jahanian, Massachusetts Institute of Technology (United States); Ramakrishna Kakarala, Picartio Inc (United States); Xiaofan Lin, A9.COM, Inc. (United States); Changsong Liu, Tsinghua University (China); Yung-Hsiang Lu, Purdue University (United States); Binu Nair, United Technologies Research Center (United States); Mu Qiao, Shutterfly, Inc. (United States); Alastair Reed, Digimarc Corporation (United States); Andreas Savakis, Rochester Institute of Technology (United States); Bin Shen, Google Inc. (United States); Wiley Wang (United States); Jane You, The Hong Kong Polytechnic University (Hong Kong, China); Buyue Zhang, Intel Corporation (United States)