Surveillance Architecture for Human Activity Recognition using Unmanned Aerial Vehicle / Arquitetura de vigilância para reconhecimento de atividade humana usando veículo aéreo não tripulado

• Autor(a) principal: Pinto, Milena F.
• Data de Publicação: 2020
• Outros Autores: Melo, Aurelio Gouvêa de, Marins, Guilherme, Biundini, Iago Z., Marcato, André L. M.
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Brazilian Applied Science Review
• Texto Completo: https://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/9981
• topic: Intelligent Systems; UAV; Robotic Systems; Surveillance; Semi-Autonomous Mission.

There is intensive growth in researches regarding surveillance and threat detection. Surveillance tasks often involve several actors with multiple interactions. Thus, modeling a complex activity becomes challenging. This work proposes an architecture comprised of low, middle, and high levels. The low-level recognizes characteristics, positioning of objects, and time of occurrences utilizing a camera and Unmanned Aerial Vehicle (UAV) sensors. The middle-level is responsible for structuring the information from the low-level using Deterministic Finite Automata (DFA). An expert system attached in the high-level module performs inference over the organized information to enables the system to have simple reasoning modules, assisting the operator decision. The architecture is embedded in a UAV to reduce the number of cameras and to reach difficult areas. The experiments showed that the proposed system updated the grammatical structure effectively, given a sequence of information computed by the vision modules.