Egocentric Dataset of the University of Barcelona – Segmentation (EDUB-Seg) is a dataset for egocentric event segmentation acquired by the Narrative Clip, which takes a picture every 30 seconds. Our Narrative dataset, named Egocentric Dataset of the University of Barcelona – Segmentation, contains a total of 18,735 images captured by 7 different users during overall 20 days. To ensure diversity, all users were wearing the camera in different contexts: while attending a conference, on holiday, during the weekend, and during the week.
The ground truth (GT) segmentations provided are included in the folder GT. In each column a segmentation performed by a different annotator is included. Each row represents a segment in the day set, and is indicated by the initial frame and the final frame separated by a blank space. The following criteria was used to generate the annotations:
An event is a semantically perceptual unit that can be inferred by visual features, without any prior knowledge of what the camera wearer is actually doing.
If you use this dataset or any of the provided GT segmentations for any purpose, please, do not forget to cite the following papers:
 Talavera E, Dimiccoli M, Bolaños M, Aghaei M, Radeva P. “R-clustering for egocentric video segmentation.” In Iberian Conference on Pattern Recognition and Image Analysis 2015 Jun 17 (pp. 327-336). Springer International Publishing.
 Dimiccoli M, Bolaños M, Talavera E, Aghaei M, Nikolov SG, Radeva P. “SR-Clustering: Semantic Regularized Clustering for Egocentric Photo Streams Segmentation.” In Computer Vision and Image Understanding Journal (CVIU). arXiv preprint arXiv:1512.07143. 2015 Dec 22.
If you have any doubt or proposal, please, do not hesitate to contact any of the first two authors: