Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability

Autor:	Sweeney, Lorin, Matran-Fernandez, Ana, Halder, Sebastian, de Herrera, Alba G. Seco, Smeaton, Alan, Healy, Graham
Rok vydání:	2021
Předmět:	Quantitative Biology - Neurons and Cognition Computer Science - Human-Computer Interaction Computer Science - Machine Learning Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	The aim of the Memorability-EEG pilot subtask at MediaEval'2021 is to promote interest in the use of neural signals -- either alone or in combination with other data sources -- in the context of predicting video memorability by highlighting the utility of EEG data. The dataset created consists of pre-extracted features from EEG recordings of subjects while watching a subset of videos from Predicting Media Memorability subtask 1. This demonstration pilot gives interested researchers a sense of how neural signals can be used without any prior domain knowledge, and enables them to do so in a future memorability task. The dataset can be used to support the exploration of novel machine learning and processing strategies for predicting video memorability, while potentially increasing interdisciplinary interest in the subject of memorability, and opening the door to new combined EEG-computer vision approaches. Comment: 3 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2201.00620 Zobrazit plný text záznamu View this record from Arxiv