Informatics and Telematics Institute, CERTH

Marina Riga, Georgios Petkos, Symeon Papadopoulos, Emmanouil Schinas, Yiannis Kompatsiaris

CERTH @ 2014 MediaEval Social Event Detection Task

Challenge 1 Goal

• Cluster all images in the test set, so that each cluster corresponds to a social event

Approach

• Same event model (SEM) predicts if a pair of images belong to the same cluster

(based on set of per-modality similarities)

• Organize images in graph according to the predictions of the SEM

• Select candidate neighbours using appropriate indices for scalability

• Cluster the graph using a community detection algorithm to obtain the clusters

Key tweak

• False positive predictions of the SEM are much more important for the task than false negatives

• Tune the SEM so that we obtain a higher true positives rate at the cost of a somewhat lower

true negatives rate

Results

• Without tweak F1 is 0.4514 and NMI is 0.7594. With tweak F1 is 0.9161 and NMI is 0.9818

Challenge 2 Goal

• Retrieve all events matching a set of criteria (type, location, time, involved entities)

Approach

• Crawl Flickr to obtain data related to the criteria and build language models for each of them

• Also collect a general dataset on which we build a reference language model

• An event i is classified using the specific language models and the general language model

according to: pspecific(i) / pgeneral (i) > θ

• Alternative approach: pspecific, general(i) / pgeneral (i) > θ

• For location in particular, we use a grid-based location estimation approach [3]

Results

• Alternative classification approach with tuning of threshold using the training set gave the best

results: F1 was 0.4604 (with an average Recall of 0.3915 and an average Precision of 0.7080)

• Average F1 when considering only queries that contain location criteria was 0.6331

[ ] G. Petkos, “. Papadopoulos, Y. Ko patsiaris. “ocial eve t detectio usi g ulti odal clusteri g a d i tegrati g supervisory sig als . ICMR . [ ] G. Petkos, “. Papadopoulos, E. “chi as, Y. Ko patsiaris. Graph-based multimodal clustering for social event detection in large collectio s of i ages . MMM 2014.

[ ] A. Popescu. CEA lists’ participatio at MediaEval placi g task. MediaEval .