%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/07.11.13.34
%2 sid.inpe.br/sibgrapi/2016/07.11.13.34.27
%@doi 10.1109/SIBGRAPI.2016.036
%T Detecting crowd features in video sequences
%D 2016
%A Favaretto, Rodolfo Migon,
%A Dihl, Leandro,
%A Musse, Soraia Raupp,
%@affiliation Pontifícia Universidade Católica do Rio Grande do Sul
%@affiliation Pontifícia Universidade Católica do Rio Grande do Sul
%@affiliation Pontifícia Universidade Católica do Rio Grande do Sul
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I IEEE Computer Society´s Conference Publishing Services
%J Los Alamitos
%S Proceedings
%K image processing, fundamental diagrams, classification, crowd analysis.
%X We propose a new methodology to detect social aspects of crowds in video sequences based on pedestrian features, which are obtained through image processing/computer vision techniques. The main idea is to apply and extend the concepts of Fundamental Diagram (FD) with more features, such as grouping and collectivity. Using crowd features we identify the crowd type and the main characteristics. In addition, we also investigated two further results: the visual assessment of people in real video sequences in order to detect crowd characteristics, and the usage of our method to detect similarity of crowds in videos.
%@language en
%3 PID4344647.pdf