access icon free Hot spot method for pedestrian detection using saliency maps, discrete Chebyshev moments and support vector machine

© The Institution of Engineering and Technology
Received 07/03/2017, Accepted 10/03/2018, Revised 21/02/2018, Published 13/03/2018

The increasing risks of border intrusions or attacks on sensitive facilities and the growing availability of surveillance cameras lead to extensive research efforts for robust detection of pedestrians using images. However, the surveillance of borders or sensitive facilities poses many challenges including the need to set up many cameras to cover the whole area of interest, the high bandwidth requirements for data streaming and the high-processing requirements. Driven by day and night capabilities of the thermal sensors and the distinguished thermal signature of humans, the authors propose a novel and robust method for the detection of pedestrians using thermal images. The method is composed of three steps: a detection which is based on a saliency map in conjunction with a contrast-enhancement technique, a shape description based on discrete Chebyshev moments and a classification step using a support vector machine classifier. The performance of the method is tested using two different thermal datasets and is compared with the conventional maximally stable extremal regions detector. The obtained results prove the robustness and the superiority of the proposed framework in terms of true and false positives rates and computational costs which make it suitable for low-performance processing platforms and real-time applications.

Inspec keywords: infrared imaging; pedestrians; temperature sensors; temperature measurement; video surveillance; cameras; image sensors; reliability; image classification; image enhancement; support vector machines

Other keywords: pedestrian detection; hot spot method; maximally stable extremal region detector; border intrusion; shape description; discrete Chebyshev moment; thermal signature; contrast-enhancement technique; data streaming; saliency map; surveillance camera; thermal sensor; image classification; thermal imaging; support vector machine classifier

Subjects: Image recognition; Knowledge engineering techniques; Computer vision and image processing techniques; Image sensors; Reliability; Thermal variables measurement

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