%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/07.20.20.01
%2 sid.inpe.br/sibgrapi/2016/07.20.20.01.40
%@doi 10.1109/SIBGRAPI.2016.049
%T MSKDE - Using Marching Squares to Quickly Make High Quality Crime Hotspot Maps
%D 2016
%A Queiroz Neto, Jose Florencio de,
%A Santos, Emanuele Marques dos,
%A Vidal, Creto Augusto,
%@affiliation Federal University of Ceará
%@affiliation Federal University of Ceará
%@affiliation Federal University of Ceará
%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 Hotspot maps, Visualization.
%X In recent years, violence has considerably increased in the world. In a certain state of Brazil, for example, the homicide rate grew from 16 homicides per 100,000 inhabitants in 2000, to 48 homicides per 100,000 inhabitants in 2014. Police departments worldwide use various types of crime maps, which are generated with diverse techniques, in order to analyze and fight crime. Those types of maps enable decision makers to identify high-risk areas and to allocate resources more effectively. Hotspot maps, in particular, are crime maps often available in visual interactive systems for crime analysis. In order for hotspot maps to be really useful, they need to be very accurate - specially for resource allocation tasks - and to be processed very fast for quick analysis of different scenarios. In this paper, we propose MSKDE - Marching Squares Kernel Density Estimation, a solution for generating fast and accurate hotspot maps. We describe the technique and demonstrate its superior qualities through a careful comparison with the standard Kernel Density Estimation technique, which is widely used for generating hotspot maps.
%@language en
%3 PID4370329.pdf