TCNJ-CS@MediaEval 2017 Emotional Impact of Movie Task

نویسنده

  • Sejong Yoon
چکیده

This paper presents our approaches for the MediaEval Emotional Impact of Movies Task. We employed features from image frames and audio signal. We use support vector regression for the learning and prediction. In addition, we introduce a new feature using exponential decay of the initially predicted emotion labels. The motivation behind this is to computationally model lingering effect. Experimental results and future direction are also discussed.

برای دانلود رایگان 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

TCNJ-CS@MediaEval 2017 Predicting Media Interestingness Task

In this paper, we present our approach and investigation on the MedialEval 2017 Predicting Media Interestingness Task. We used most of the visual and audiotory features provided. The standard kernel fusion technique was applied to combine features and we used the ranking support vector machine to learn the classification model. No extra data was introduced to train the model. Official results, ...

متن کامل

BOUN-NKU in MediaEval 2017 Emotional Impact of Movies Task

In this paper, we present our approach for the Emotional Impact of Movies task of Mediaeval 2017 Challenge, involving multimodal fusion for predicting arousal and valence for movie clips. In our system, we have two pipelines. In the first one, we extracted audio/visual features, and used a combination of PCA, Fisher vector encoding, feature selection, and extreme learning machine classifiers. I...

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

HKBU at MediaEval 2017 - Emotional Impact of Movies Task

In this paper, we describe our model designed for automatic prediction of emotional impact of movies. Specifically, a two-stage learning framework is proposed. First, the dimensionality reduction techniques are employed to discover the key emotion information embedded in the original feature space. Specifically, we use a classical method principal component analysis (PCA) and a new algorithm bi...

متن کامل

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

ذخیره در منابع من


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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017