DocumentCode :
2012152
Title :
Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor
Author :
Goto, Kunihiro ; Kidono, Kiyosumi ; Kimura, Yoshikatsu ; Naito, Takashi
Author_Institution :
Toyota Central R&D Labs., Inc., Nagakute, Japan
fYear :
2011
fDate :
5-9 June 2011
Firstpage :
224
Lastpage :
229
Abstract :
This paper proposes a pedestrian detection and direction estimation method by the cascade approach with multiclassifiers using the Feature Interaction Descriptor (FIND). FIND describes the high-level properties of an object´s appearance by computing pair-wise interactions of adjacent regionlevel features. To perform efficient and accurate detection using FIND, we employ the cascade approach with multiclassifiers specialized in both the direction of a pedestrian and the distance of the pedestrian from a camera. Using this framework, the developed system can improve the detection performance and provide information of the direction of a pedestrian simultaneously. The experimental results show that superior detection performance and direction estimation results were obtained by our method.
Keywords :
driver information systems; image classification; image sensors; object detection; camera; cascade detector; direction estimation; feature interaction descriptor; multiclassifiers; pairwise adjacent region level feature interactions; pedestrian detection; Cameras; Computational efficiency; Detectors; Estimation; Feature extraction; Histograms; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2011 IEEE
Conference_Location :
Baden-Baden
ISSN :
1931-0587
Print_ISBN :
978-1-4577-0890-9
Type :
conf
DOI :
10.1109/IVS.2011.5940432
Filename :
5940432
Link To Document :
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