Photo Selection for Family Album using Deep Neural Networks

The development of digital cameras and the web booming are the critical reasons for the increasing of digital portraits. However, such kind of daily photos are usually too many to select and organize, which leads to further requirement of better photo management services. In this paper, we are focusing on a significant part of daily photos -- family photos. We collaborate with a family photo service provider, Chikaku Inc., to create a family photo dataset. The dataset contains 12,140 images with corresponding rates (from 1 to 5) measuring if it is suitable to be selected for a family album. According to our experiments on classifying eligibility of the photos as a printed family photo album, the classification accuracy reaches 96.6% on the test set.