| Vol-1984 urn:nbn:de:0074-1984-7 Copyright © 2017 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

# MediaEval 2017
Multimedia Benchmark Workshop

### Working Notes Proceedings of the MediaEval 2017 Workshop
co-located with the Conference and Labs of the Evaluation Forum (CLEF 2017)

### Dublin, Ireland, September 13-15, 2017.

Edited by

### Guillaume Gravier (1)
Benjamin Bischke (2)
Claire-Hélène Demarty (3)
Maia Zaharieva (4)
Michael Riegler (5)
Emmanuel Dellandrea (6)
Dmitry Bogdanov (7)
Richard Sutcliffe (8)
Gareth J.F. Jones (9)
Martha Larson (10)

(1) CNRS, IRISA, France
(2) German Research Center for Artificial Intelligence (DFKI), Germany
(3) Technicolor, France
(4) Vienna University of Technology, Austria
(5) Simula Research Laboratory and University of Oslo, Norway
(6) École Centrale de Lyon, LIRIS, France
(7) Music Technology Group, Universitat Pompeu Fabra, Spain
(8) University of Essex, UK
(9) Dublin City University, Ireland
(10) Delft University of Technology & Radboud Univeristy, Netherlands

## Table of Contents

### Multimedia Satellite

#### Overview paper:

- The Multimedia Satellite Task at MediaEval 2017
  Benjamin Bischke, Patrick Helber, Christian Schulze, Venkat Srinivasan, Andreas Dengel, Damian Borth

#### Working notes papers:

- Convolutional Neural Networks for Disaster Images Retrieval
  Sheharyar Ahmad, Kashif Ahmad, Nasir Ahmad, Nicola Conci
- WISC at MediaEval 2017: Multimedia Satellite Task
  Nataliya Tkachenko, Arkaitz Zubiaga, Rob Procter
- Multi-modal Deep Learning Approach for Flood Detection
  Laura Lopez-Fuentes, Joost van de Weijer, Marc Bolaños, Harald Skinnemoen
- CNN and GAN Based Satellite and Social Media Data Fusion for Disaster Detection
  Kashif Ahmad, Konstantin Pogorelov, Michael Riegler, Nicola Conci, Pål Halvorsen
- A Domain-based Late-Fusion for Disaster Image Retrieval from Social Media
  Minh-Son Dao, Quang-Nhat-Minh Pham, Duc-Tien Dang-Nguyen
- Visual and Textual Analysis of Social Media and Satellite Images for Flood Detection @ Multimedia Satellite Task MediaEval 2017
  Konstantinos Avgerinakis, Anastasia Moumtzidou, Stelios Andreadis, Emmanouil Michail, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris
- Data-Driven Flood Detection using Neural Networks
  Keiller Nogueira, Samuel Fadel, Ícaro Dourado, Rafael Werneck, Javier Muñoz, Otávio Penatti, Rodrigo Calumby, Lin Li, Jefersson Dos Santos, Ricardo Torres
- Retrieving Social Flooding Images Based on Multimodal Information
  Zhengyu Zhao, Martha Larson
- Flood detection using Social Media Data and Spectral Regression based Kernel Discriminant Analysis
  Muhammad Hanif, Muhammad Atif Tahir, Mahrukh Khan, Muhammad Rafi
- BMC@MediaEval 2017 Multimedia Satellite Task via Regression Random Forest
  Xiyao Fu, Yi Bin, Liang Peng, Jie Zhou, Yang Yang, Heng Tao Shen
- Detection of Flooding Events in Social Multimedia and Satellite Imagery using Deep Neural Networks
  Benjamin Bischke, Prakriti Bhardwaj, Aman Gautam, Patrick Helber, Damian Borth, Andreas Dengel

### Predicting Media Interestingness

#### Overview paper:

- MediaEval 2017 Predicting Media Interestingness Task
  Claire-Hélène Demarty, Mats Sjöberg, Bogdan Ionescu, Thanh-Toan Do, Michael Gygli, Ngoc Q.K. Duong

#### Working notes papers:

- The IITB Predicting Media Interestingness System for MediaEval 2017
  Jayneel Parekh, Harshvardhan Tibrewal, Sanjeel Parekh
- DA-IICT at MediaEval 2017: Objective Prediction of Media Interestingness
  Rashi Gupta, Manish Narwaria
- Multimodality and Deep Learning when Predicting Media Interestingness
  Eloïse Berson, Claire-Hélène Demarty, Ngoc Q.K. Duong
- Predicting Media Interestingness via Biased Discriminant Embedding and Supervised Manifold Regression
  Yang Liu, Zhonglei Gu, Tobey H. Ko
- TCNJ-CS@MediaEval 2017 Predicting Media Interestingness Task
  Sejong Yoon
- GIBIS at MediaEval 2017: Predicting Media Interestingness Task
  Jurandy Almeida, Ricardo Savii
- DUT-MMSR at MediaEval 2017: Predicting Media Interestingness Task
  Reza Aditya Permadi, Septian Gilang Permana Putra, Helmiriawan, Cynthia C. S. Liem
- LAPI at MediaEval 2017 - Predicting Media Interestingness
  Mihai Gabriel Constantin, Boteanu Bogdan Andrei, Bogdan Ionescu
- EURECOM @MediaEval 2017: Media Genre Inference for Predicting Media Interestingness
  Olfa Ben-Ahmed, Jonas Wacker, Alessandro Gaballo, Benoit Huet
- RUC at MediaEval 2017: Predicting Media Interestingness Task
  Shuai Wang, Shizhe Chen, Jinming Zhao, Wenxuan Wang, Qin Jin

### Retrieving Diverse Social Images

#### Overview paper:

- Retrieving Diverse Social Images at MediaEval 2017: Challenges, Dataset and Evaluation
  Maia Zaharieva, Bogdan Ionescu, Alexandru Lucian Gînscă, Rodrygo L.T. Santos, Henning Müller

#### Working notes papers:

- UMONS @ MediaEval 2017: Diverse Social Images Retrieval
  Omar Seddati, Nada Ben Lhachemi, Stéphane Dupont, Saïd Mahmoudi
- CFM@MediaEval 2017 Retrieving Diverse Social Images Task via Re-ranking and Hierarchical Clustering
  Liang Peng, Yi Bin, Xiyao Fu, Jie Zhou, Yang Yang, Heng Tao Shen
- NLE@MediaEval’17: Combining Cross-Media Similarity and Embeddings for Retrieving Diverse Social Images
  Jean-Michel Renders, Gabriela Csurka
- LAPI @ 2017 Retrieving Diverse Social Images Task: A Pseudo-Relevance Feedback Diversification Perspective
  Bogdan Boteanu, Mihai Gabriel Constantin, Bogdan Ionescu
- Rank Fusion and Multimodal Per-topic Adaptiveness for Diverse Image Retrieval
  Rodrigo Calumby, Iago Araujo, Felipe Cordeiro, Fabiana Bertoni, Sérgio Canuto, Fabiano Belém, Marcos Gonçalves, Icaro Dourado, Javier Munoz, Lin Li, Ricardo Torres
- Exploiting Visual-based Intent Classification for Diverse Social Image Retrieval
  Bo Wang, Martha Larson

### Medico

#### Overview paper:

- Multimedia for Medicine: The Medico Task at MediaEval 2017
  Michael Riegler, Konstantin Pogorelov, Pål Halvorsen, Kristin Ranheim Randel, Sigrun Losada Eskeland, Duc-Tien Dang-Nguyen, Mathias Lux, Carsten Griwodz, Concetto Spampinato, Thomas de Lange

#### Working notes papers:

- HKBU at MediaEval 2017 - Medico: Medical Multimedia Task
  Yang Liu, Zhonglei Gu, William K. Cheung
- An Inception-like CNN Architecture for GI Disease and Anatomical Landmark Classification
  Stefan Petscharnig, Klaus Schöffmann, Mathias Lux
- SCL-UMD at the Medico Task-MediaEval 2017: Transfer Learning based Classification of Medical Images
  Taruna Agrawal, Rahul Gupta, Saurabh Sahu, Carol Espy Wilson
- Ensemble of Texture Features for Finding Abnormalities in the Gastro-Intestinal Tract
  Syed Sadiq Ali Naqvi, Shees Nadeem, Muhammad Zaid, Muhammad Atif Tahir
- A Comparison of Deep Learning with Global Features for Gastrointestinal Disease Detection
  Konstantin Pogorelov, Michael Riegler, Pål Halvorsen, Carsten Griwodz, Thomas de Lange, Kristin Ranheim Randel, Sigrun Losada Eskeland, Duc-Tien Dang-Nguyen, Olga Ostroukhova, Mathias Lux, Concetto Spampinato

### Emotional Impact of Movies

#### Overview paper:

- The MediaEval 2017 Emotional Impact of Movies Task
  Emmanuel Dellandréa, Martijn Huigsloot, Liming Chen, Yoann Baveye, Mats Sjöberg

#### Working notes papers:

- MIC-TJU in MediaEval 2017 Emotional Impact of Movies Task
  Yun Yi, Hanli Wang, Jiangchuan Wei
- TCNJ-CS@MediaEval 2017 Emotional Impact of Movie Task
  Sejong Yoon
- THUHCSI in MediaEval 2017 Emotional Impact of Movies Task
  Zitong Jin, Yuqi Yao, Ye Ma, Mingxing Xu
- BOUN-NKU in MediaEval 2017 Emotional Impact of Movies Task
  Nihan Karslioglu, Yasemin Timar, Albert Ali Salah, Heysem Kaya
- HKBU at MediaEval 2017 - Emotional Impact of Movies Task
  Yang Liu, Zhonglei Gu, Tobey H. Ko

### AcousticBrainz Genre

#### Overview paper:

- The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources
  Dmitry Bogdanov, Alastair Porter, Julián Urbano, Hendrik Schreiber

#### Working notes papers:

- MediaEval 2017 AcousticBrainz Genre Task: Multilayer Perceptron Approach
  Khaled Koutini, Alina Imenina, Matthias Dorfer, Alexander Gruber, Markus Schedl
- Hierarchical Multilabel Classification and Voting for Genre Classification
  Benjamin Murauer, Maximilian Mayerl, Michael Tschuggnall, Eva Zangerle, Martin Pichl, Günther Specht
- Single and Multi Column Neural Networks for Content-based Music Genre Recognition
  Chang Wook Kim, Jaehun Kim, Kwangsub Kim, Minz Won
- DNN in the AcousticBrainz Genre Task 2017
  Nicolas Dauban
- ICSI in MediaEval 2017 Multi-Genre Music Task
  Kijung Kim, Jaeyoung Choi

### C@MERATA

#### Overview paper:

- The C@merata task at MediaEval 2017: Natural Language Queries about Music, their JSON Representations, and Matching Passages in MusicXML Scores
  Richard Sutcliffe, Donncha Ó Maidín, Eduard Hovy

#### Working notes papers:

- The CLAS System at the MediaEval 2017 C@merata Task
  Stephen Wan
- The DMUN System at the MediaEval 2017 C@merata Task
  Andreas Katsiavalos

2017-11-06: submitted by Guillaume Gravier, metadata incl. bibliographic data published under Creative Commons CC0
2017-11-07: published on CEUR-WS.org |valid HTML5|