Real-time tracking method for infrared image target with multi-feature fusion

Abstract

The invention discloses a real-time tracking method for an infrared image target with multi-feature fusion. The real-time tracking method comprises the following steps of: initializing a target tracking point position; initializing a target model; calculating a target candidate model; calculating a coefficient of unified feature Bhattacharyya and weight coefficients between feature; calculating a new tracking position of a current frame target; estimating the coefficient of the unified feature Bhattacharyya at the new position; and comparing the two coefficients of the unified feature Bhattacharyya and outputting results. The real-time tracking method can be used for adaptively calculating the weight coefficients between multiple features, enhances the robustness of target tracking, ensures the stability of target tracking, solves the problem of tracking point drifting caused by unstable single feature, and effectively improves the accuracy of target tracking.

Description

technical field [0001] The invention designs a multi-feature fusion infrared image target tracking method, in particular to an infrared image target tracking method suitable for real-time hardware implementation. Background technique [0002] In recent years, with the development of integrated circuit technology and infrared materials, infrared imaging technology has made great progress and has been widely used in national defense construction and national economy. However, compared with visible light images, infrared images have relatively low signal-to-noise ratios, so they can only provide limited information for target detection and tracking in infrared images. Due to the inconspicuous characteristics of the target in the infrared image and the existence of large background clutter, it becomes more difficult to accurately track the target in the infrared image. [0003] Currently, object tracking algorithms are divided into two categories: model-based tracking methods a...

AI Technical Summary

Problems solved by technology

Therefore, the existing target tracking algorithms have the following disadvantages: (1) The classic target tracking algorithm uses a single feature to describe the target, which has poor anti-interference ability; (2) Most existing multi-feature target tracking algorithms only use the current frame to calculate When the target undergoes complex changes, the robustness of the tracking algorithm is poor; (3) Most of the existing tracking algorithms, when the target has non-rigid deformation, partial occlusion and overlap, the tracking accuracy decreases, and even the target is lost; (4) Most of the existing tracking algorithms greatly increase the complexity of the algorithm while improving the target tracking accuracy, which is not easy to realize in real time by hardware

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