Pedestrian detection based on maximally stable extremal regions

This paper presents a new approach to generate hypotheses about the presence of pedestrians in an infrared image. Information about maximally stable extremal regions is used to locate the warmest regions on the image, which are considered to be potential human heads. To capture the complete human bo...

Full description

Saved in:
Bibliographic Details
Published in2010 IEEE Intelligent Vehicles Symposium pp. 910 - 914
Main Authors Frolov, Vadim, Puente Leon, Fernando
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2010
Subjects
Cameras
Humans
Infrared detectors
Infrared imaging
Infrared sensors
Laser radar
Sensor fusion
Shape
Support vector machine classification
Support vector machines
Online AccessGet full text

Cover

More Information
Summary:This paper presents a new approach to generate hypotheses about the presence of pedestrians in an infrared image. Information about maximally stable extremal regions is used to locate the warmest regions on the image, which are considered to be potential human heads. To capture the complete human body, these regions are scaled based on the range data of a lidar sensor. Closely related regions are merged into one bigger region to avoid the segmentation which arises from the heterogeneous heating emission of a dressed human. Additionally, the area and perimeter of each potential pedestrian are examined to discard artificial objects. The optimal decision measure is sought so that all pedestrians are extracted from a scene. All remaining hypotheses should be further processed with a statistical classifier.
ISBN:1424478669
9781424478668
ISSN:1931-0587
2642-7214
DOI:10.1109/IVS.2010.5548023