Context Understanding from Query-Based Streaming Video

Abstract

Context understanding is established from the content, analysis, and guidance from query-based coordination between users and machines. In this chapter, a live video computing (LVC) structure is presented for access of a database management of information for context assessment. Context assessment includes multimedia fusion of query-based text, images, and exploited tracks which can be utilized for content-based image retrieval (CBIR). In this chapter, we explore the developments in database systems to enable context to be utilized in user-based queries (e.g., Level 5 fusion) for information fusion content extraction. Using a common video dataset, we demonstrate time savings in the analysis from user queries to provide a context, privacy, and semantic-aware information fusion.