title: Pedestrian detection in far-infrared daytime images using a hierarchical codebook of SURF.
abstract: One of the main challenges in intelligent vehicles concerns pedestrian detection for driving assistance. Recent experiments have showed that state-of-the-art descriptors provide better performances on the far-infrared (FIR) spectrum than on the visible one, even in daytime conditions, for pedestrian classification. In this paper, we propose a pedestrian detector with on-board FIR camera. Our main contribution is the exploitation of the specific characteristics of FIR images to design a fast, scale-invariant and robust pedestrian detector. Our system consists of three modules, each based on speeded-up robust feature (SURF) matching. The first module allows generating regions-of-interest (ROI), since in FIR images of the pedestrian shapes may vary in large scales, but heads appear usually as light regions. ROI are detected with a high recall rate with the hierarchical codebook of SURF features located in head regions. The second module consists of pedestrian full-body classification by using SVM. This module allows one to enhance the precision with low computational cost. In the third module, we combine the mean shift algorithm with inter-frame scale-invariant SURF feature tracking to enhance the robustness of our system. The experimental evaluation shows that our system outperforms, in the FIR domain, the state-of-the-art Haar-like Adaboost-cascade, histogram of oriented gradients (HOG)/linear SVM (linSVM) and MultiFtrpedestrian detectors, trained on the FIR images.
authors: Diotasoft, 15 Boulevard Emile Baudot, Massy 91300, France. bbe@diotasoft.com.
authors: Bassem
authors: B
authors: Besbes
authors: LITIS Laboratory, National Institute of Applied Sciences, 76801 Saint-Etienne-du-Rouvray Cedex, France. adela@cs.ubbcluj.ro.
authors: Alexandrina
authors: A
authors: Rogozan
authors: LITIS Laboratory, National Institute of Applied Sciences, 76801 Saint-Etienne-du-Rouvray Cedex, France. adela@cs.ubbcluj.ro.|Faculty of Computer Science, Babes-Bolyai University, Kogalniceanu no.1, Cluj-Napoca RO-400084, Romania. adela@cs.ubbcluj.ro.
authors: Adela-Maria
authors: AM
authors: Rus
authors: LITIS Laboratory, National Institute of Applied Sciences, 76801 Saint-Etienne-du-Rouvray Cedex, France. abdelaziz.bensrhair@insa-rouen.fr.
authors: Abdelaziz
authors: A
authors: Bensrhair
authors: Dipartimento di Ingegneria dell' Informazione, Universita di Parma, Parco Area delle Scienze, Parma 181/a 43124, Italy. broggi@vislab.it.
authors: Alberto
authors: A
authors: Broggi