%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16c/2017/12.01.19.44
%2 sid.inpe.br/mtc-m16c/2017/12.01.19.44.12
%@issn 2179-4820
%T A statistical method for detecting move, stop, and noise episodes in trajectories
%D 2017
%A Nogueira, Tales P.,
%A Martin, Hervé,
%A Andrade, Rossana M. C.,
%@affiliation Universitè Grenoble Alpes
%@affiliation Universitè Grenoble Alpes
%@affiliation Universidade Federal do Ceará (UFC)
%E Davis Jr., Clodoveu A. (UFMG),
%E Queiroz, Gilberto R. de (INPE),
%B Simpósio Brasileiro de Geoinformática, 18 (GEOINFO)
%C Salvador
%8 04-06 dez. 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 210-221
%S Anais
%X Detecting stops is an important task in trajectory analysis. Stops can reveal interesting aspects of a moving object behavior such as its daily routine, bottlenecks in traffic jams, or visiting times of touristic places. In order to record those traces, trajectories must be sampled and, in some cases, post-processed. This process from collecting raw data to storing them may vary according to the devices and applications that collect the data. Another important charac- teristic in many trajectories is the presence of noisy segments, a fact is often ignored by most stop detection methods. In this work, we present a method that exploits gaps in time and space to identify episodes of movement, stop, and pe- riods where some classification is inconclusive, which we define as noise. In addition, our method does not rely on contextual information as opposed to some current methods, which makes our proposal also suitable for trajectories recorded in free space.
%@language pt
%3 29nogueira_andrade.pdf