Lifelogging cameras capture everyday life from a first-person perspective,
but generate so much data that it is hard for users to browse and organize
their image collections effectively. In this paper, we propose to use automatic
image captioning algorithms to generate textual representations of these
collections. We develop and explore novel techniques based on deep learning to
generate captions for both individual images and image streams, using temporal
consistency constraints to create summaries that are both more compact and less
noisy. We evaluate our techniques with quantitative and qualitative results,
and apply captioning to an image retrieval application for finding potentially
private images. Our results suggest that our automatic captioning algorithms,
while imperfect, may work well enough to help users manage lifelogging photo
collections.

提出使用深度学习技术和自动图像字幕生成算法来生成 Lifelogging 摄像机捕捉到的图片的文本表示，通过应用时间一致性约束来创建更加简洁和不含噪声的摘要，研究结果表明，自动字幕生成算法可以帮助用户管理 Lifelogging 照片集合。