TY  - JOUR
AU  - Stefan Lonn
AU  - Petia Radeva
AU  - Mariella Dimiccoli
PY  - 2019//
TI  - Smartphone picture organization: A hierarchical approach
T2  - CVIU
JO  - Computer Vision and Image Understanding
SP  - 102789
VL  - 187
N2  - 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.
UR  - https://doi.org/10.1016/j.cviu.2019.07.009
L1  - http://refbase.cvc.uab.es/files/LRD2019.pdf
N1  - MILAB; no proj
ID  - Stefan Lonn2019
ER  -