Comparing two methods of object detection in autonomous vehicle

Author

Rosas-Miranda, Dario Ivan ; Ponomaryov, Volodymyr ; Palacios-Enriquez, Alfredo Eduardo

Author_Institution

ESIME, Inst. Politec. Nac., Mexico City, Mexico

fYear

2014

fDate

Sept. 29 2014-Oct. 3 2014

Firstpage

1

Lastpage

6

Abstract

Autonomous obstacle avoidance in mobile robots has been an active field in image processing and control theory. In this paper, we propose and evaluate two methods for multiple objects detection for a mobile robot in outdoor. The first method uses a block matching algorithm to obtain a disparity map and SURF features detector. The second method uses a semi-global stereo vision environment. Both methods are tested during detecting pedestrian, boxes and cones using a video sequence in validation of a robot.

Keywords

collision avoidance; feature extraction; image matching; image sequences; mobile robots; object detection; robot vision; stereo image processing; video signal processing; SURF features detector; autonomous obstacle avoidance; autonomous vehicle; block matching algorithm; box detection; cone detection; control theory; disparity map; image processing; mobile robots; object detection; pedestrian detection; semi-global stereo vision environment; speeded-up robust features; video sequence; Algorithm design and analysis; Detectors; Feature extraction; Mobile robots; Mutual information; Object detection; Robustness; Disparity Map; Object Detection; Stereo Vision;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering, Computing Science and Automatic Control (CCE), 2014 11th International Conference on

Conference_Location

Campeche

Print_ISBN

978-1-4799-6228-0

Type

conf

DOI

10.1109/ICEEE.2014.6978279

Filename

6978279