%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/08.15.21.28
%2 sid.inpe.br/sibgrapi/2016/08.15.21.28.25
%T The Good, The Fast and The Better Pedestrian Detector
%D 2016
%A Jordão, Artur,
%A Schwartz, William Robson,
%@affiliation DCC-UFMG
%@affiliation DCC-UFMG
%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 Sociedade Brasileira de Computação
%J Porto Alegre
%S Proceedings
%K Oblique Decision Tree, Partial Least Squares, Filtering Approaches, High-Level Information, Fusion of Detectors.
%X Pedestrian detection is a well-known problem in Computer Vision, mostly because of its direct applications in surveillance, transit safety and robotics. In the past decade, several efforts have been performed to improve the detection in terms of accuracy, velocity and enhancement of features. In this work, we proposed and analyzed techniques focusing on these points. Firstly, we propose an accurate oblique random forest associated with Partial Least Squares (PLS). The method consists on utilize the PLS to find a decision surface at each node in a decision tree. Secondly, we evaluate filtering approaches to reduce the search space and keep only potential regions of interest to be presented to detectors, speeding up the detection process. Finally, we propose a novel approach to extract powerful features regarding the scene. The method combines results of distinct pedestrian detectors by reinforcing the human hypothesis whereas suppressing a significant number of false positives.
%@language en
%3 Main.pdf