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Target tracking method and electronic equipment
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A technology of target tracking and electronic equipment, applied in the electronic field, can solve the problems of being unable to judge whether the tracking target is lost, difficult to find the tracking target, etc.
Active Publication Date: 2017-05-10
NINEBOT (BEIJING) TECH CO LTD
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[0004] The embodiment of the present invention provides a target tracking method and electronic equipment, which solves the technical problems that the online learning visual tracking method in the prior art cannot judge whether the tracking target is lost, and it is difficult to retrieve the tracking target after the tracking is lost.
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Embodiment 1
[0102] This embodiment provides a target tracking method, which is applied to electronic equipment, and the electronic equipment can be: ground robots (for example: balance cars), or unmanned aerial vehicles (for example: multi-rotor drones, or fixed-wing drones) Human-machine), or electric vehicles and other equipment, here, this embodiment does not specifically limit what kind of equipment the electronic equipment is. Wherein, the electronic device has an image acquisition unit (for example, a camera), and the image acquisition unit is used to acquire image data.
[0103] like figure 1 As shown, the target tracking method includes:
[0104] Step S101: Determine a tracking target in the initial frame image of the image data.
[0105] As an optional embodiment, step S101 includes:
[0106] When the initial frame image is output through the display screen, the user's selection operation is obtained; based on the user's selection operation, the tracking target is determined i...
Embodiment 2
[0163] This embodiment provides an electronic device, the electronic device has an image acquisition unit, and the image acquisition unit is used to acquire image data, such as Figure 8 As shown, the electronic equipment, including:
[0164] A first determining unit 801, configured to determine a tracking target in the initial frame image of the image data;
[0165] An extraction unit 802, configured to extract a plurality of candidate targets in a subsequent frame image of the image data, where the subsequent frame image is any frame image after the initial frame image;
[0166] A calculation unit 803, configured to calculate the similarity between each candidate target and the tracking target;
[0167] The second determining unit 804 is configured to determine, among the plurality of candidate targets, the candidate target having the highest similarity with the tracking target as the tracking target.
[0168] As an optional embodiment, the first determining unit 801 inclu...
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Abstract
The invention discloses a target tracking method which is applied to electronic equipment. The electronic equipment is provided with an image acquisition unit which is used for acquiring image data. The method comprises the steps that a tracking target is determined in the initial frame of image of the image data; multiple candidate targets are extracted in the subsequent frame of image of the image data, wherein the subsequent frame of image is any frame of image after the initial frame of image; the similarity of each candidate target and the tracking target is calculated; and the candidate target having the highest similarity with the tracking target in the multiple candidate targets is determined to be the tracking target. The technical problems in the prior art that an online learning visual tracking method cannot judge lost of the tracking target and the tracking target is difficult to find after lost of tracking target can be solved. Meanwhile, the invention also discloses the electronic equipment.
Description
technical field [0001] The invention relates to the field of electronic technology, in particular to a target tracking method and electronic equipment. Background technique [0002] After the rise of visual tracking technology based on online learning in recent years, it has become a hot spot in visual tracking. This type of method extracts feature templates according to the tracking target specified in the initial frame without any prior experience of offline learning, and trains the model for tracking the target in subsequent videos. During the tracking process, according to the tracking status Update the model to adapt to the target's pose changes. This type of method does not require any offline training, can track any object specified by the user, and has high versatility. [0003] However, due to the single feature and template of the tracking target, it is difficult to judge whether the target is lost during the tracking process of the target; and after the target i...
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