Evangelos Alexiou has been working as a Doctoral Assistant in the Multimedia Signal Processing Group (MMSPG) at EPFL since July 2016, under the supervision of Prof. Touradj Ebrahimi. His research interests include multimedia, video compression and transmission, image processing, and communication systems. Currently he is working on quality assessment and compression of point cloud representation.
Evangelos Alexiou was born in Thessaloniki, Greece, on September 18th, 1986. He received his diploma in Electronic and Computer Engineering from the faculty of Technical University of Crete (TUC) in 2011. He received his M.Sc degree in Signal Processing for Communications and Multimedia from the faculty of National and Kapodistrian University of Athens (DI) in 2013. From November 2012 to September 2015, he was involved in a research program, namely MusiNet, with topic the comprehensive design and implementation of a networked music performance system under the supervision of Professor Alexandros Eleftheriadis.
Geometry-only point cloud data set
A series of studies was conducted to investigate the performance of state-of-the-art objective quality metrics and propose new subjective and objective evaluation methodologies. For this purpose, a representative set of geometry-only point clouds was assembled and degraded using two different types of distortions.
In this webpage, we make publicly available a dataset consisting of the reference point cloud models, degraded stimuli, and subjective quality scores that were collected in two experimental setups.
Visual attention for point clouds in VR
An eye-tracking experiment was conduced in an immersive virtual reality environment with 6 degrees of freedom, using a head mounted display. The users interacted with 3D point cloud models following a task-dependent protocol, while recording their gaze and head trajectories.
In this webpage, we make publicly available a dataset consisting of the tracked behavioural data, post-processing results, saliency maps in form of importance weights, re-distribution of a sub-set of contents and scripts to generate the exact versions of the point clouds that were used in the study, and usage examples.
Quality assessment for point cloud compression
A large-scale rigorous analysis of visual quality for widely-used point cloud models subject to compression artifacts introduced by the state-of-the-art MPEG point cloud codecs (V-PCC and G-PCC variants) was performed. The codecs were benchmarked using both subjective and objective quality assessment methodologies, and best-practices for geometry-only and geometry-plus-color encoding were subjectively evaluated. For this purpose, a total of three experiments were carried in two inter-continental laboratories.
In this webpage, we make publicly available quality scores associated with the stimuli under assessment for each experiment. For purposes of reproducibility, a content that was used while not being part of established point cloud repositories adopted by standardisation bodies, is re-distributed. Moreover, scripts are provided in order to generate the reference models and the rendering-related meta-data that were used in this study.
Point cloud web renderer
In this repository, an open source web-based point cloud renderer is made publicly open. The renderer is developed on top of the well-established three.js library, ensuring compatibility across different devices and operating systems. The renderer supports visualization of point clouds with real-time interaction, while viewing conditions can be easily configured. The user is able to choose between either an adaptive, or a fixed splat size rendering mode in order to display the models. The renderer supports both PLY and PCD point cloud file formats. The current settings have been optimized for voxelized contents, without this limiting its usage, since any point cloud can be displayed independently of its geometric structure (i.e., regular or irregular).