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"ACM SIGCHI General Interest Announcements (Mailing List)" <[log in to unmask]>
Mon, 10 Apr 2017 09:24:07 +0200
"M. Larson" <[log in to unmask]>
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"M. Larson" <[log in to unmask]>
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MediaEval 2017: Multimedia Evaluation Shared-Tasks
Regular Registration Deadline: 1 May

MediaEval (Benchmarking Initiative for Multimedia Evaluation) offers 
shared-tasks to the multimedia research community involving images, 
text, video, and audio/music. The tasks address cutting-edge multimedia 
challenges (multimedia retrieval, access and exploration) with a clear 
human or social aspect.

Further information and the link for registration is available at:

Short descriptions of the tasks are below. Task results will be 
presented at the MediaEval 2017 Workshop, 13-15 September in Dublin, 
Ireland, co-located with CLEF 2017.

Deadline for regular registration: 1 May 2017

Late registration is possible after 1 May, but may narrow the window 
that you have to work with the data. See data release deadlines for the 
individual tasks at

MediaEval 2017 Tasks:

*Retrieving Diverse Social Images Task*
Create an image retrieval system that is capable of returning 
diversified lists of results in response to complex queries.

*Emotional Impact of Movies Task*
Design/implement a (multimodal) classifier to predict the emotion 
induced by a movie clip. This year we expand to detecting content that 
causes fear in kids.

*Predicting Media Interestingness Task*
Design/implement an algorithm that predicts interesting frames or clips 
of a movie/video that help viewers decide which content to watch.

*Multimedia Satellite Task*
Social images can be used to enrich events that are detected by remote 
sensing. Create an image retrieval system that retrieves images that 
depict flooding on the ground, and align them with evidence of flooding 
in satellite images.

*Medico: Medical Multimedia Task*
Design/implement a classifier that is able to detect diseases in videos 
taken inside the intestines. Automatically generate appropriate captions.

*AcousticBrainz Genre Task: Content-based music genre recognition from 
multiple sources* Create a genre prediction system for music capable of 
leveraging labels from multiple information sources.

*C@MERATA: Querying Musical Scores with English Noun Phrases Task*
Create a system which accepts as input a natural language phrase 
referring to a musical feature (e.g., ‘consecutive fifths’) and outputs 
a list of passages in a music score which contain that feature.

For more information see 
and/or check out the report on the 2016 workshop:

M. Larson, M. Soleymani, G. Gravier, B. Ionescu, G.J.F. Jones. 2017. The 
Benchmarking Initiative for Multimedia Evaluation: MediaEval 2016. IEEE 
Multimedia, Vol. 24, No. 1, 93-96

If you have further questions, please contact: Martha Larson 
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