Vehicle detection using multimodal imaging sensors from a moving platform

Christopher N. Dickson, Andrew Michael Wallace, Matthew Kitchin, Barry Connor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

A modular vehicle detection system, using a two-stage hypothesis generation (HG) and hypothesis combination (HC) approach is presented. The HG stage consists of a set of simple algorithms which parse multi-modal data and provide a set of possible vehicle locations. These hypotheses are subsequently fused in a combination stage. This modular design allows the system to utilise additional modalities where available, and the combination of multiple information sources is shown to reduce false positive detections. The system uses Thales' high-resolution long wave infrared polarimeter and a four-band visible/near infrared multispectral system. Vehicle cues are taken from motion ow vectors, thermal intensity hot spots, and regions with a locally high degree of linear polarisation. Results using image sequences gathered from a moving vehicle are shown, and the performance of the system is assessed with Receiver Operator Characteristics.
Original languageEnglish
Title of host publicationElectro-Optical and Infrared Systems
Subtitle of host publicationTechnology and Applications IX
EditorsDavid A. Huckridge, Reinhard R. Ebert
PublisherSPIE
ISBN (Print)9780819492821
DOIs
Publication statusPublished - 24 Oct 2012

Publication series

NameProceedings of SPIE
PublisherSPIE
Volume8541
ISSN (Print)0277-786X

Fingerprint

Dive into the research topics of 'Vehicle detection using multimodal imaging sensors from a moving platform'. Together they form a unique fingerprint.

Cite this