AMV 2019

Special session: Machine Learning in Advanced Machine Vision (AMV2019)

Monday, 16th of December (TBC)

A special session in conjunction with ICMLA2019 in Boca Raton, Florida, USA.

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We are proud to present a special session on Machine learning in Advanced Machine Vision (AMV2019). This special session is organized in conjunction with ICMLA2019 and taking place in Boca Raton, Florida, USA. It is scheduled on Monday the 16th of December 2019 (TBC) (all-day workshop).

A large variety of industrially oriented applications (e.g. quality control, pick and place) have in the past decades been successfully implemented throughout a wide range of industries. These implementations are characterized by very controlled surroundings and objects (e.g. CAD models of objects available, controlled lighting). Advanced Machine Vision refers to computer vision and machine learning - based systems where such assumptions do not hold, for example, when handling biological objects as seen in the food-production industry or when operating outdoors. With recent advancements in sensing and processing power, the potential for further automation in industry based on computer vision and machine learning is clearly present. Furthermore, the exploding domain of computer vision and machine learning algorithms (e.g. deep learning) provides dozens of new opportunities. However, there is in general a major gap between the topics in focus at major international computer vision and machine learning conferences and the actual industrial needs. More often approaches are hardly transferable into practical and robust solutions for industrial challenges. The ambition of this workshop is to close this gap, by bringing together both academics and practitioners from the field.

The special session will take place at the ICMLA2019 conference venue.


Call For Papers

Please find a pdf version of this call for papers by clicking here

The ambition of this full-day AMV2019 special session is to bring together practitioners and researchers from different disciplines related to Advanced Machine Vision to share ideas and methods on current and future use of computer vision and machine learning algorithms in real-life and industrially relevant systems. This field raises the need of applied research that focusses on the technology transfer from academics towards practitioners, yielding several challenges like top-notch accuracies, real-time processing, minimal training data, minimal manual input, user-friendly interfaces, …

To this end we welcome contributions with a strong focus on (but not limited to) the following topics within Advanced Machine Vision:

  • Data input sources

    • Data fusion
    • Multi-modal data
  • Improving robustness of algorithms

    • Real-time performance
    • Non-controlled illumination
    • Non-trivial intra object variability
    • Top-notch accuracies
  • Removing or reducing the need of training data

    • Data augmentation
    • Artificial data
  • Processing power and memory requirements

  • Obtaining training data and ground truth annotations

  • Lab testing versus inline testing

  • Transfer learning towards new applicational domains

  • Deep learning for advanced machine vision

  • Quality assessment of non-trivial objects

  • Real-life and industrially relevant applications

The special session has a best paper award of 700 euro sponsored by ROBOVISION.

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Submission

Authors are encouraged to submit high-quality, original (i.e. not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop) research.

Papers submitted for reviewing should be conform to IEEE specifications. Manuscript templates can be downloaded from the IEEE website.

Papers are limited to 8 pages. All the papers will go through double-blind peer review process. Authors names and affiliations should not appear in the submitted paper. Authors prior work should be cited in the third person. Authors should also avoid revealing their identities and/or institutions in the text, figures, links, etc. A paper should be submitted to one track only. Submission of the same paper to multiple tracks will result in rejection of the paper.

After review, authors will either be accepted as regular papers (with an oral presentation) or as short papers (with a poster presentation).

  • Regular papers should be up to 6 pages long. Authors of regular papers can add up to 2 extra pages, at an additional cost of $50 per page. A regular paper cannot be more than 8 pages long. References and any other additional material must be included in this number of pages.

  • Short papers should be up to 4 pages long. Authors of short papers can add up to 2 extra pages, at an additional cost of $50 per page. A short paper cannot be more than 6 pages long. References and any other additional material must be included in this number of pages.

All submissions are handled through the CMT submission website of the ICMLA2019 conference: CLICK HERE FOR SUBMISSION Make sure that you select the correct workshop (Machine Learning in Advanced Machine Vision) at the top left corner of the CMT submission website, when hitting the button “new submission”.

Authors are requested to submit their paper in a single PDF file (maximum file size 20MB). Submission of supplementary material is optional (up to 100MB). Accepted file formats for supplementary material are: PDF, PNG, JPG, GIF, ZIP, MP4, WMV, MPEG or AVI.

For questions/remarks regarding the submission e-mail: steven[dot]puttemans[at]kuleuven[dot]be.


Important Dates

  • Paper submission deadline: September 7, 2019 (11:59 CEST)
  • Notification of acceptance + reviews available: October 7, 2019
  • Camera-ready papers & pre-registration deadline: October 17, 2019
  • The ICMLA conference: December 16-19, 2019

People

Workshop Organizers


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Thomas B. Moeslund
Professor
Visual Analysis of People Lab
Aalborg University
Denmark

Website: click here
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Rikke Gade
Assistant Professor
Visual Analysis of People Lab
Aalborg University
Denmark

Website: click here
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Toon Goedeme
Professor
EAVISE Research Group
KU Leuven
Belgium

Website: click here
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Steven Puttemans
Post-doctoral researcher
EAVISE Research Group
KU Leuven
Belgium

Website: click here
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Ajmal Mian
Professor
School of Physics, Mathematics & Computing, The University of Western Australia
Australia

Website: click here

Supporting universities and research labs


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Program Committee


The organizing committee would like to thank all members of the program committee for the work they invest in assuring that our AMV2019 special session at ICMLA2019 achieves a high-quality standard!


Program

Invited speakers

other keynote speakers will be announced soon

1) Fatih Porikli

Talk title

Biography

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Fatih Porikli has received his Ph.D. from New York University (NYU) in 2002. He is an IEEE Fellow and a Professor in the Research School of Engineering, Australian National University (ANU). He is also serving as the Technical Vice President at Futurewei Device & Hardware in San Diego. He led the Computer Vision Research Group Leader at NICTA, Australia and managed projects as the Distinguished Research Scientist at Mitsubishi Electric Research Laboratories, Cambridge. He developed satellite imaging solutions at HRL, Malibu CA, and 3D display systems at AT&T Research Laboratories, Middletown, NJ. His research interests include computer vision, deep learning, manifold learning, online learning, and image enhancement with commercial applications in smartphones, AR/VR, autonomous vehicles, video surveillance, defense, and medical systems. He received the R&D 100 Scientist of the Year Award in 2006, won six best paper awards at scientific events and recognized with six professional prizes at his industrial appointments. He authored more than 200 publications, co-edited two books, and invented 73 US patents. He has been an Associate Editor of several IEEE and Springer journals for the past 15 years.

Tentative program

to be announced