Filter updating method, device and intelligent terminal in target tracking
A target tracking and updating method technology, applied in the field of computer vision, can solve the problem that the filter update coefficient cannot be adaptively adapted to the tracking target, and the tracking accuracy is poor.
Active Publication Date: 2019-12-31
HISENSE
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[0007] In order to solve the limitation in the related art that the filter update coefficient cannot adaptively adapt to the change of the tracking target, and if the tracking target changes during the target tracking process, the technical problem of poor tracking accuracy, the present disclosure provides a Filter updating method, device and intelligent terminal in target tracking
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[0035] Here, an exemplary embodiment will be described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present invention. On the contrary, they are only examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.
[0036] figure 1 It is a block diagram of a device 100 shown in the present disclosure according to an exemplary embodiment, and the device 100 can be used as an implementation environment involved in the present disclosure.
[0037] For example, the device 100 may be a terminal device such as a smart phone, a desktop computer, a smart TV, a notebook computer, and a tablet comp...
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The present invention discloses a filter update method and device in target tracking. The method comprises: determining the maximum response value corresponding to image features in the current frame video image in the target tracking of the video image; obtaining the filter update coefficient corresponding to the current frame video image through the maximum response value according to the negative correlation between maximum response value and the filter update coefficient; and updating the filter corresponding to the current frame video image according to the filter update coefficient. The maximum response value corresponding to the image features can represent the state corresponding to the current target tracking in the current frame video image, and there is an implied relation between the maximum response value and the filter update coefficient, and therefore, the filter update coefficient capable of adapting to the changing of the target tracking the current frame video image according to the negative correlation between maximum response value and the filter update coefficient so as to greatly improve the tracking accuracy, and the filter update coefficient can adapts the changing of the tracking target change in the self-adaption mode.
Description
Technical field [0001] The present disclosure relates to the field of computer vision technology, and in particular to a filter update method, device and smart terminal in target tracking. Background technique [0002] Target tracking has always been a research hotspot in the field of computer video due to its wide application. At present, many target tracking methods have emerged to realize target tracking in video images. However, these target tracking methods do not consider timeliness, that is, the processing speed of applying these target tracking methods to each frame is too slow to meet real-time requirements, especially when the image resolution is slightly larger. [0003] In response to this problem, Bolme et al. applied the relevant filtering ideas in signal processing to target tracking for the first time to obtain a faster tracking speed and thus have a strong timeliness. However, because the original image is directly used as the image feature, the tracking accuracy...
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IPC IPC(8): G06T7/246
CPCG06T7/20G06T2207/10016G06T2207/20024
Inventor 高伟杰陈雪冷佳旭
Owner HISENSE