@article{bacha_event_2016,

title = {Event recognition in photo albums using probabilistic graphical models and feature relevance},

author = {S. Bacha and M. S. Allili and N. Benblidia},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992111208&doi=10.1016%2fj.jvcir.2016.07.021&partnerID=40&md5=20ebb156819c8fcae6e28949046ceb6e},

doi = {10.1016/j.jvcir.2016.07.021},

issn = {10473203 (ISSN)},

year  = {2016},

date = {2016-01-01},

booktitle = {Proceedings - International Conference on Pattern Recognition},

journal = {Journal of Visual Communication and Image Representation},

volume = {40},

number = {Part B},

pages = {546–558},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper proposes a method for event recognition in photo albums which aims at predicting the event categories of groups of photos. We propose a probabilistic graphical model (PGM) for event prediction based on high-level visual features consisting of objects and scenes, which are extracted directly from images. For better discrimination between different event categories, we develop a scheme to integrate feature relevance in our model which yields a more powerful inference when album images exhibit a large number of objects and scenes. It allows also to mitigate the influence of non-informative images usually contained in the albums. The performance of the proposed method is validated using extensive experiments on the recently-proposed PEC dataset containing over 61 000 images. Our method obtained the highest accuracy which outperforms previous work. © 2016 Elsevier Inc.},

note = {Publisher: Academic Press Inc.},

keywords = {Event prediction, Event recognition, Feature relevance, Graphic methods, Object/scene relevance, Photo album, Photo albums, Probabilistic graphical models, Probabilistic graphical models (PGM), Speech recognition, Visual feature},

pubstate = {published},

tppubtype = {article}

}