Lifelogging Retrieval based on Semantic Concepts Fusion

Lifelogging data provides useful insight understanding about our lives during daily activities. Thus, it is essential to develop a system to assist users to retrieve events or memories from lifelogging data from ad-hoc text queries. In this paper, we first propose a method to process lifelogging data by grouping images into visual shots and clusters, then extract semantic concepts on scene category and attributes, entities, and actions. We then develop a query system that supports 4 main types of query conditions: temporal, spatial, entity and action, and extra data criteria. Our system is expected to efficiently assist users to search for past moments in daily logs.