# Smartphone picture organization: A hierarchical approach

## TL;DR

This paper introduces a hierarchical method for automatically organizing large, unstructured smartphone photo collections into topics and categories using probabilistic models and neural networks, improving user satisfaction.

## Contribution

It presents a novel hierarchical approach combining probabilistic Latent Semantic Analysis and CNNs for organizing smartphone photos into meaningful topics and categories.

## Key findings

- Improved organization accuracy over existing methods
- Successful estimation of latent photo topics
- Enhanced user satisfaction with the organization

## Abstract

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 10 persons. Experimental results demonstrate better user satisfaction with respect to state of the art solutions in terms of organization.