M-VIVIE: A multi-thread video indexer via identity extraction

In this work we present M-VIVIE, a system for video sequence indexing based on the identity of appearing subjects, which exploits a multithread architecture for fast processing. The system is composed of more conceptual component modules, each performing a specific kind of processing. Each module can possibly be substituted with a different one performing the same task. Special attention is devoted to classification and clustering activities. M-VIVIE presents a number of peculiarities, that distinguish it from existing systems with similar goals. Among these, the account for the concomitant appearance of two identities in the same clip, and the use of such information in the process of identity mapping. M-VIVIE was tested on different kinds of real video clips to assess both its efficacy and efficiency.