Абстрактный

Indexing For Sequential Stochastic Mechanism- Based Movement Replicas In Recognition Of Human Activity

G.Karthika, V.Bhuvaneswari

Today, numerous applications require the ability to monitor a continuous stream of fine-grained data for the occurrence of certain high-level activities. A number of computerized systems—including ATM networks, web servers, and intrusion detection systems—systematically track every atomic action they perform, thus generating massive streams of timestamped observation data, possibly from multiple concurrent activities. In this paper, address the problem of slowly indexing large number of observations and also the identification problem. A solution to this important problem would greatly benefit a broad range of applications, including fraud detection, video surveillance, and cyber security. In Existing work, tMAGIC has to be used for indexing activities and also used tMAGIC-evidence for evidence problem.We propose a Active merge algorithm to solve time complexity problem and sequence algorithm to solve identification problem.