TY  - JOUR
AU  - Mariella Dimiccoli
AU  - Marc Bolaños
AU  - Estefania Talavera
AU  - Maedeh Aghaei
AU  - Stavri G. Nikolov
AU  - Petia Radeva
PY  - 2017//
TI  - SR-Clustering: Semantic Regularized Clustering for Egocentric Photo Streams Segmentation
T2  - CVIU
JO  - Computer Vision and Image Understanding
SP  - 55
EP  - 69
VL  - 155
N2  - While wearable cameras are becoming increasingly popular, locating relevant information in large unstructured collections of egocentric images is still a tedious and time consuming processes. This paper addresses the problem of organizing egocentric photo streams acquired by a wearable camera into semantically meaningful segments. First, contextual and semantic information is extracted for each image by employing a Convolutional Neural Networks approach. Later, by integrating language processing, a vocabulary of concepts is defined in a semantic space. Finally, by exploiting the temporal coherence in photo streams, images which share contextual and semantic attributes are grouped together. The resulting temporal segmentation is particularly suited for further analysis, ranging from activity and event recognition to semantic indexing and summarization. Experiments over egocentric sets of nearly 17,000 images, show that the proposed approach outperforms state-of-the-art methods.
UR  - https://doi.org/10.1016/j.cviu.2016.10.005
L1  - http://refbase.cvc.uab.es/files/DBT2015.pdf
UR  - http://dx.doi.org/10.1016/j.cviu.2016.10.005
N1  - MILAB; 601.235
ID  - Mariella Dimiccoli2017
ER  -