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Mean-Shift tracking algorithm based on distance-weighted histogram

A weighted histogram and tracking algorithm technology, applied in the field of UAV navigation, can solve the problems of affecting real-time performance and easy loss of targets

Inactive Publication Date: 2017-03-22
张长隆
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AI Technical Summary

Problems solved by technology

[0003] Mean-Shift as an efficient target tracking algorithm has been widely used in the field of target tracking. The literature proposes a method of invariant moments, but the calculation of moment features is complicated and seriously affects the real-time performance of the Mean-Shift tracking algorithm; literature A contour tracking algorithm based on Mean-Shift and edge detection is proposed. However, when the target is deformed or occluded by this algorithm, the target is easily lost; an improved mean shift algorithm based on the target color feature is also proposed in the literature. No matter the target point conforming to the color template is given the same maximum weight regardless of its probability in the histogram, so that the target can become the density extreme area to the maximum extent to overcome the influence of interference. However, when the target moves faster in this algorithm , the target is easily lost

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  • Mean-Shift tracking algorithm based on distance-weighted histogram
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  • Mean-Shift tracking algorithm based on distance-weighted histogram

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Embodiment Construction

[0041] HSV Color Space (HSV Color Space)

[0042] HSV is a color space created based on the intuitive characteristics of colors such as hue H, saturation S, and brightness V [9] , also known as the hexagonal pyramid model. The RGB color model is a color model suitable for hardware imaging display, and the model more suitable for human visual characteristics is the HSV color model introduced below, such as figure 1 As shown, the hexagonal boundaries represent hue, the horizontal axis represents purity, and lightness is measured along the vertical axis.

[0043] HSV is chosen as the color model for target tracking because it has the following advantages [10]. First of all, it conforms to the human eye's perception of color. Secondly, when using the RGB color model, changing a certain color attribute, such as hue, must change the three coordinates of R, G, and B; while using the HSV color model, only the H coordinate needs to be changed. Finally, the HSV color space is a uni...

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Abstract

The invention discloses a Mean-Shift tracking algorithm based on a distance-weighted histogram, which belongs to the field of unmanned aerial vehicle navigation. The algorithm can accurately and stably track a moving object in a video in real time. Compared with a classical Mean-Shift algorithm, the processing time is slightly increased, but the algorithm can still meet a real-time requirement. When a target moves fast, the improved algorithm can still track the target accurately, which is much better than the classical tracking algorithm. The next step focuses on how to automatically select the window width of a kernel function, so that a tracking frame can automatically adjust as the target size changes.

Description

technical field [0001] The invention belongs to the field of unmanned aerial vehicle navigation. Specifically, it involves a Mean-Shift tracking algorithm based on distance weighted histogram. Background technique [0002] Target tracking is widely used in traffic monitoring, video coding, robot visual navigation and military industry. When the target moves quickly, the target is deformed and blocked, how to track the target of interest in the video sequence robustly and effectively has always been a problem for computers. Key points and difficulties in the field of vision research. [0003] Mean-Shift as an efficient target tracking algorithm has been widely used in the field of target tracking. The literature proposes a method of invariant moments, but the calculation of moment features is complicated and seriously affects the real-time performance of the Mean-Shift tracking algorithm; literature A contour tracking algorithm based on Mean-Shift and edge detection is prop...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/246
Inventor 张长隆刘欢敏
Owner 张长隆
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