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Sensors 2016, 16(6), 820;

Pedestrian Detection at Day/Night Time with Visible and FIR Cameras: A Comparison

Autonomous University of Barcelona, Cerdanyola, Barcelona 08193, Spain
Computer Vision Center, Cerdanyola, Barcelona 08193, Spain
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 17 March 2016 / Revised: 28 May 2016 / Accepted: 30 May 2016 / Published: 4 June 2016
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)
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Despite all the significant advances in pedestrian detection brought by computer vision for driving assistance, it is still a challenging problem. One reason is the extremely varying lighting conditions under which such a detector should operate, namely day and nighttime. Recent research has shown that the combination of visible and non-visible imaging modalities may increase detection accuracy, where the infrared spectrum plays a critical role. The goal of this paper is to assess the accuracy gain of different pedestrian models (holistic, part-based, patch-based) when training with images in the far infrared spectrum. Specifically, we want to compare detection accuracy on test images recorded at day and nighttime if trained (and tested) using (a) plain color images; (b) just infrared images; and (c) both of them. In order to obtain results for the last item, we propose an early fusion approach to combine features from both modalities. We base the evaluation on a new dataset that we have built for this purpose as well as on the publicly available KAIST multispectral dataset. View Full-Text
Keywords: far infrared; day/nighttime; pedestrian detection far infrared; day/nighttime; pedestrian detection

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González, A.; Fang, Z.; Socarras, Y.; Serrat, J.; Vázquez, D.; Xu, J.; López, A.M. Pedestrian Detection at Day/Night Time with Visible and FIR Cameras: A Comparison. Sensors 2016, 16, 820.

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