Name
Abstract | ||
|---|---|---|
This paper proposes a paradigm in the forensic area for detecting and categorizing human activities. The presented approach uses five base variables, referred to as 4W1H ("Who," "When," "What," "Where," and "How") to describe the context in an environment. The proposed system uses self-organizing maps to classify movements for the "How" variable of 4W1H, as well as particle swarm optimization clustering techniques for the grouping (clustering) of data obtained from observations. The paper describes the hardware settings required for detecting these variables and the system designed to do the sensing. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.20965/jaciii.2011.p0793 | JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS |
Keywords | Field | DocType |
self organizing maps, particle swarm optimization, 4W1H, activity recognition | Particle swarm optimization,Activity recognition,Pattern recognition,Computer science,Self-organizing map,Multi-swarm optimization,Artificial intelligence | Journal |
Volume | Issue | ISSN |
15 | 7 | 1343-0130 |
Citations | PageRank | References |
1 | 0.36 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leon Palafox | 1 | 36 | 4.93 |
| Hideki Hashimoto | 2 | 68 | 10.43 |