AUTH-SGP in MediaEval 2016 Emotional Impact of Movies Task

نویسندگان

  • Anastasia-Theodora Timoleon
  • Leontios J. Hadjileontiadis
چکیده

This paper presents all the aspects expected for the MediaEval Workshop. The tested and adopted solutions are well described and the interest of using a set of features versus another one is discussed. The conclusion follows state-ofthe-art findings and allows bringing new inputs in the understanding of emotion prediction.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The MediaEval 2016 Emotional Impact of Movies Task

This paper provides a description of the MediaEval 2016 ”Emotional Impact of Movies” task. It continues builds on previous years’ editions of the Affect in Multimedia Task: Violent Scenes Detection. However, in this year’s task, participants are expected to create systems that automatically predict the emotional impact that video content will have on viewers, in terms of valence and arousal sco...

متن کامل

BUL in MediaEval 2016 Emotional Impact of Movies Task

This paper describes our working approach for the Emotional Impact of Movies task of MediaEval 2016. There are 2 sub-tasks set to make affective predictions, based on Arousal and Valence values, on video clips. Sub-task 1 requires global emotion prediction. Here a framework is developed using Deep Auto-Encoders, a feature variation algorithm and a Deep network. For sub-task 2, a set of audio fe...

متن کامل

The MediaEval 2017 Emotional Impact of Movies Task

This paper provides a description of the MediaEval 2017 “Emotional Impact of Movies task". It continues to build on previous years’ editions. In this year’s task, participants are expected to create systems that automatically predict the emotional impact that video content will have on viewers, in terms of valence, arousal and fear. Here we provide a description of the use case, task challenges...

متن کامل

THU-HCSI at MediaEval 2016: Emotional Impact of Movies Task

In this paper we describe our team’s approach to MediaEval 2016 Challenge “Emotional Impact of Movies”. Except for the baseline features, we extract audio features and image features from video clips. We deploy Convolutional Neural Network (CNN) to extract image features and use OpenSMILE toolbox to extract audio ones. We also study multi-scale approach at different levels aiming at the continu...

متن کامل

RUC at MediaEval 2016 Emotional Impact of Movies Task: Fusion of Multimodal Features

In this paper, we present our approaches for the Mediaeval Emotional Impact of Movies Task. We extract features from multiple modalities including audio, image and motion modalities. SVR and Random Forest are used as our regression models and late fusion is applied to fuse different modalities. Experimental results show that the multimodal late fusion is beneficial to predict global affects and...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016