%0 Journal Article
%T Smartphone picture organization: A hierarchical approach
%A Stefan Lonn
%A Petia Radeva
%A Mariella Dimiccoli
%J Computer Vision and Image Understanding
%D 2019
%V 187
%F Stefan Lonn2019
%O MILAB; no proj
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3297), last updated on Tue, 25 Jan 2022 12:02:14 +0100
%X We live in a society where the large majority of the population has a camera-equipped smartphone. In addition, hard drives and cloud storage are getting cheaper and cheaper, leading to a tremendous growth in stored personal photos. Unlike photo collections captured by a digital camera, which typically are pre-processed by the user who organizes them into event-related folders, smartphone pictures are automatically stored in the cloud. As a consequence, photo collections captured by a smartphone are highly unstructured and because smartphones are ubiquitous, they present a larger variability compared to pictures captured by a digital camera. To solve the need of organizing large smartphone photo collections automatically, we propose here a new methodology for hierarchical photo organization into topics and topic-related categories. Our approach successfully estimates latent topics in the pictures by applying probabilistic Latent Semantic Analysis, and automatically assigns a name to each topic by relying on a lexical database. Topic-related categories are then estimated by using a set of topic-specific Convolutional Neuronal Networks. To validate our approach, we ensemble and make public a large dataset of more than 8,000 smartphone pictures from 40 persons. Experimental results demonstrate major user satisfaction with respect to state of the art solutions in terms of organization.
%U https://doi.org/10.1016/j.cviu.2019.07.009
%U http://refbase.cvc.uab.es/files/LRD2019.pdf
%P 102789