This paper aims to present a new approach to implement a pedestrian tracking algorithm for a passive automotive night vision application.
First, the basic information of passive and active night vision systems is presented, with implementation methods adopted in previous work. The proposed thermal‐image processing is a combination of seed detection, boundary detection and seed growth computations, based on a temperature thresholding scheme.
The processing routine performance is assessed when implemented to a continuous sequence of thermal acquisitions, from a commercial automotive night vision module. Experimental results show good tracking performance for both pedestrians and passing vehicles.
A strategy of multi‐seed growth, directional seed growth and image fusion is proposed to improve the current tracking algorithm.
New thermal image processing routines are applied to commercial, automotive night vision modules, to provide robust pedestrian tracking at real‐time processing speed.
