A Two-Level Lifelog Search Engine at the LSC 2019

Abstract

The rise of affordable wearable devices makes visual lifelog data easier to collect. This data can then be retrieved as an aside memory usable as well for people with memory issues or in daily life to be more efficient. This paper presents the retrieval system designed for the Lifelog Search Challenge 2019 competition. This retrieval system offers two search levels: a semantic one and an image-based one. The data used for the indexing for both levels (semantic data for the text-based method or combinations of HSV Histogram and BRIEF features for the example-based one) as well as the architecture of the overall system is described. Results from our experiments are promising. The text-based search engine has disparate results that strongly depend on the keywords used for the query. For the example search engine, the best features are composed of both HSV histogram and BRIEF features. Despite encouraging results, the processing time appears to be a limitation.