Pedestrian detection in infrared images using Aggregated Channel Features

Author

Brehar, Raluca ; Vancea, Cristian ; Nedevschi, Sergiu

Author_Institution

Comput. Sci. Dept., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania

fYear

2014

fDate

4-6 Sept. 2014

Firstpage

127

Lastpage

132

Abstract

We propose a method for detecting pedestrians in infrared images. The method combines a fast region of interest generator with fast feature pyramid object detection. Knowing the appearance model of pedestrians in infrared images we infer some edge and intensity based filters that generate the regions in which pedestrian hypotheses may appear. On those regions we apply the Aggregated Channel Features introduced by [1]. We train and test the proposed solution on an infrared pedestrian data set and the results show a good detection accuracy and small execution time of about 30fps.

Keywords

infrared imaging; object detection; pedestrians; aggregated channel features; edge based filters; fast feature pyramid object detection; infrared images; infrared pedestrian data set; intensity based filters; interest generator; pedestrian detection; pedestrian hypotheses; Accuracy; Feature extraction; Generators; Gray-scale; Histograms; Image edge detection; Intelligent vehicles; Aggregated Channel Features; Infrared Images; Pedestrian detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computer Communication and Processing (ICCP), 2014 IEEE International Conference on

Conference_Location

Cluj Napoca

Print_ISBN

978-1-4799-6568-7

Type

conf

DOI

10.1109/ICCP.2014.6936964

Filename

6936964