Part based pedestrian detection based on Logic inference

This paper presents an approach on detection of largely occluded pedestrians. From a pair of synchronized cameras in the Visible Light (VL) and Far Infrared (FIR) spectrum individual detections are combined and final confidence is inferred using a small set of logic rules via a Markov Logic Network. Pedestrians not entirely contained in the image or occluded are detected based on the binary classification on subparts of the detection window. The presented method is applied to a pedestrian classification problem in urban environments. The classifier has been tested in an Intelligent Transportation System (ITS) platform as part of an Advanced Driver Assistance Systems (ADAS).

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Supplemental Notes:
- Abstract reprinted with permission of IEEE.
Corporate Authors:
Institute of Electrical and Electronics Engineers (IEEE)

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New York, NY United States 10016-5997
Authors:
- Olmeda, D
- Armingol, Jose Maria
- de la Escalera, A
Conference:
- 16th International IEEE Conference on Intelligent Transportation Systems (ITSC)
- Location: The Hague , Netherlands
- Date: 2013-10-6 to 2013-10-9
Publication Date: 2013-10

Language

English

Media Info

Media Type: Web
Features: References;
Pagination: pp 1364-1369
Monograph Title: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

Subject/Index Terms

TRT Terms: Cameras; Driver support systems; Intelligent transportation systems; Logic; Markov processes; Pedestrian detectors; Pedestrians; Urban areas
Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Vehicles and Equipment; I72: Traffic and Transport Planning; I91: Vehicle Design and Safety;

Filing Info

Accession Number: 01563474
Record Type: Publication
ISBN: 9781479929146
Files: TRIS
Created Date: May 18 2015 11:03AM