Localization and tracking of closely-spaced human targets based on infrared sensors

Abstract

In recent years, indoor human localization and tracking technology has been a research hotspot. However, the problem caused by closely-spaced targets is often avoided for target localization and tracking. As a common situation in real scene, it is of great research value and application prospect to find out ways to effectively solve the problem of accurately locating and tracking closely-spaced targets. Thermopile array (TPA) sensors, a kind of widely investigated infrared sensors, are often used to detect human targets, which are expected to solve the closely-spaced problem. This paper proposes a method for localization and tracking of indoor closely-spaced targets by using TPA sensors. Visual background extractor (ViBE) algorithm is used to preprocess the data and extract the infrared characteristic region of human body. Several algorithms such as connected components labelling algorithm, temperature peak method and k-means++ clustering algorithm are used to locate the closely-spaced targets. In the aspect of closely-spaced target tracking algorithm, the temperature summation of target’s infrared thermal map is used to assist the nearest neighbor data association algorithm for data association of closely-spaced targets. Kuhn-Munkres algorithm is used to match the location point and trajectory properly. The Kalman filter, the first-order particle filter and the second-order particle filter are compared and analyzed to further reduce the tracking error. Finally, the system is tested in the actual indoor scene. The experimental results show that the proposed system can achieve the goal of localization and tracking of closely-spaced targets.