Best Student Research Seminars

On this page

IS&T offers students who receive best paper conference awards an opportunity to give a free online presentation related to the work discussed in their proceedings paper (click on title to view paper). These seminars are recorded for later viewing.

Upcoming Seminars

CIC29 Best Paper

Hao Xie

G0 Revisited as Equally Bright Reference Boundary
Hao Xie, Meta Reality Labs


Read paper

In this work, brilliance and zero grayness were reexamined to scale lightness/brightness across the chromaticity diagram. Observers were asked to adjust the luminance of a color patch to appear with no grayness, or equivalently just about/cease to glow. The hypothesis was that lightness can be equalized across those chromaticities and the Helmholtz-Kohlrausch effect is automatically incorporated.

Hao Xie studied color science at Rochester Institute of Technology, where he worked with Prof. Mark Fairchild on Representing Color as Multiple Independent Scales as part of his dissertation. He is now a research scientist at Meta Reality Labs.




CIC29 Cactus Award for Best Interactive (Poster) Paper

Dipendra J. Mandal

Influence of Acquisition Parameters on Pigment Classification using Hyperspectral Imaging
Dipendra J. Mandal, Norwegian University of Science and Technology (NTNU)


Read paper

Pigment classification of paintings helps to analyze the object and to know its historical value. Hyperspectral imaging technology has been used for pigment characterization for many years and has potential in its scientific analysis. Despite its advantages, there are several challenges linked with hyperspectral image acquisition. The quality of such acquired hyperspectral data can be influenced by different parameters. This work investigated the effect of four key parameters—focus distance, signal-to-noise ratio, integration time, and illumination geometry—on pigment classification accuracy for a mockup using hyperspectral imaging in visible and near-infrared regions.

Dipendra Mandal is a PhD fellow within the CHANGE ITN Project (Cultural Heritage Analysis for New Generation) at the Norwegian University of Science and Technology (NTNU), Norway. He is working on a quality assessment of cultural heritage digitization.





CIC29 Best Student Paper

Tanzima Habib

Estimation of BRDF Measurements for Printed Colour Samples
Tanzima Habib, Norwegian University of Science and Technology (NTNU)


Read paper

This paper describes a method to estimate BRDF measurements for different printed colors, using just the BRDF measurements of the substrate and the primary inks. In this approach only four spectral measurements of each test colour are required to estimate BRDF, which reduces the number of measurements required to estimate BRDF of a printed surface and to estimate the spectral reflectances that describe its material surface characteristics.

Tanzima Habib is a final year PhD student at Norwegian University of Science and Technology where she is working on the prediction of 2.5D printing appearance and its implementation with iccMAX, the new ICC colour management architecture.



Best Paper 3D Imaging and Applications 2022
(Electronic Imaging Symposium)

Joao Prazeres

Quality Analysis of Point Cloud Coding Solutions
Joao Prazeres, Universidade da Beira Interior


Read paper

A subjective quality based comparison between four point clouds codecs is presented, using a set of six point clouds, coded with four different point cloud encoding solutions—MPEG V-PCC and G-PCC, a deep learning coding solution RS-DLPCC, and Draco— with different bit rates. A subjective test where the distorted and reference point clouds were rotated in a video sequence side-by-side followed by the quality evaluation, was conducted. Then the performance of a set of four point cloud objective quality metrics of he quality, was analysed using the subjective quality evaluation results. This talk presents the result of this work.

Joao Prazeres is a PhD candidate from Universidade da Beira Interior (UBI), Covilhã. He graduated in electrical and computer engineering from Universidade da Beira Interior in 2018 and received his master degree in 2020.






CIC29 Cactus Award for Best Interactive (Poster) Paper

Yoko Arteaga

Image-based Goniometric Appearance Characterisation of Bronze Patinas
Yoko Arteaga, Centre for Research and Restoration


Read paper

Patinas are a form of metal polychromy used to decorate metallic artworks. Due to the nature of the metallic surface, their color and gloss is perceived differently when the illumination and viewing directions vary. Sparkle effect on surfaces is a physical phenomenom caused by micro-facets on the surface coating, which are also perceived with changing viewing and illumination geometry. In this paper, a method designed for the measurement of sparkle is applied for the goniometric characterisation of bronze patinas, using a set of six different patinas, in three colors and two surface finishes.

Yoko Arteagae is a final year PhD student at the Centre for Research and Restoration of the Museums of France. She is working on characterizing surface appearance and microtopography of cultural heritage objects.

Best Paper Image Quality and Sysem Performance XIX
(Electronic Imaging Symposium 2022)

Abderrezzaq Sendjasn

Patch-based CNN Model for 360 Image Quality Assessment with Adaptive Pooling Strategies, 
Abderrezzaq Sendjasn, University of Poitiers and Norwegian University of Science and Technology (NTNU)


Read paper

360° image quality assessment using deep neural networks is usually designed using a multi-channel paradigm exploiting possible viewports, mainly due to the high resolution of such images and the unavailability of ground truth labels (subjective quality scores) for individual viewports. The multi-channel model is trained to predict the score of the whole 360° image. However, this comes with a high complexity cost as multi neural networks run in parallel. This talk discusses patch-based training. To account for the non-uniformity of quality distribution of a scene, a weighted pooling of patches’ scores is applied. The latter relies on natural scene statistics in addition to perceptual properties related to immersive environments.

Abderrezzaq Sendjasn is currently a third year PhD candidate in signal and image processing at the University of Poitiers, France, and NTNU, Norway. He received his MSc in computer science from the University of Oran 1 in Algeria in 2017. His research interests include image processing, human visual perception, image quality assessment, 360-degree images, immersive application, and deep learning.

Recordings of Past Seminars

REFLECTANCE

Predicting the Reflectance and Transmittance of Translucent Dental Resins

Vincent Duveiller, Université Jean Monnet - Saint-Etienne

Best Student Paper Award: CIC28
LUMINANCE

Effect of Peak Luminance on Perceptual Color Gamut Volume

Fu Jiang, Munsell Color Science Laboratory, Rochester Institute of Technology and Apple Inc.

Cactus Award for Best Interactive Paper: CIC28
MATERIAL APPEARANCE

Caustics and Translucency Perception

Davit Gigilashvili, Norwegian University of Science and Technology (Norway)

Best Student Paper: Material Appearance (MAAP) 2020 Conference 

Sponsored by:
Seminar Support:
anonymous donor and
3D Data Compression

Variable Precision Depth Encoding for 3D Range Geometry Compression

Matthew G. Finley, University of Iowa (US)

Seminar Support:
anonymous donor and
CMOS SENSORS

An Over 120dB Dynamic Range Linear Response Single Exposure CMOS Image Sensor with Two-stage Lateral Overflow Integration Trench Capacitors

Yasuyuki Fujihara, School of Engineering Tohoku University (Japan)

Arnaud Darmont Memorial Best Paper Award: Image Sensors and Systems (ISS) 2020 Conference 

Sponsored by
 
Seminar Support:
anonymous donor and
Change Detection

LambdaNet: A Fully Convolutional Architecture for Directional Change Detection

Bryan Blakeslee, Rochester Institute of Technology (US)

Seminar Support:
anonymous donor and
Autonomous Vehicles

Camera System Performance Derived from Natural Scenes

Oliver van Zwanenberg, University of Westminster (UK)

Seminar Support:
anonymous donor and
CNNS
CNNS

Learning a CNN on multiple sclerosis lesion segmentation with self-supervision

Alexandre Fenneteau, Siemens Healthcare (France)

Seminar Support:
anonymous donor and