Date of Original Version
Abstract or Description
Lifelog systems, inspired by Vannevar Bush’s concept of “MEMory EXtenders” (MEMEX), are capable of storing a person’s lifetime experience as a multimedia database. Despite such systems’ huge potential for improving people’s everyday life, there are major challenges that need to be addressed to make such systems practical. One of them is how to index the inherently large and heterogeneous lifelog data so that a person can efficiently retrieve the log segments that are of interest. In this paper, we present a novel approach to indexing lifelogs using activity language. By quantizing the heterogeneous high dimensional sensory data into text representation, we are able to apply statistical natural language processing techniques to index, recognize, segment, cluster, retrieve, and infer high-level semantic meanings of the collected lifelogs. Based on this indexing approach, our lifelog system supports easy retrieval of log segments representing past similar activities and generation of salient summaries serving as overviews of segments.
Computer and Systems Architecture Commons, Data Storage Systems Commons, Digital Circuits Commons, Digital Communications and Networking Commons, Hardware Systems Commons, Other Computer Engineering Commons, Other Electrical and Computer Engineering Commons, Robotics Commons, Systems and Communications Commons, VLSI and Circuits, Embedded and Hardware Systems Commons
ICMI-MLMI ’10, Beijing, China..