Target tracking method and electronic device

An electronic device, comprising:

• one or more processors;
• and
• a memory coupled to the one or more processors and configured to store instructions that, when executed by the one or more processors, cause the electronic device to be configured to:
• display a first shooting interface, wherein a first region of the first shooting interface displays a video stream shot by a camera lens;
• receive a first operation, when the first region displays an nth frame of image of the video stream, provided to the nth frame of image by a user, wherein n is a positive integer;
• perform feature extraction on the nth frame of image, in response to the first operation, to obtain a template feature, wherein the nth frame of image comprises a target;
• select a first tracking region from an (n+x)th frame of image of the video stream, wherein x is a positive integer;
• and
• search the first tracking region through a first convolutional neural network (CNN) based on the template feature, and output a first position and a first confidence that corresponds to the first position, wherein whether the (n+x)th frame of image comprises the target is based on the first confidence,
• wherein if the first confidence indicates that the (n+x)th frame of image does not comprise the target, the electronic device is further configured to search the first tracking region through a second CNN based on the template feature, and output a second position and a second confidence that corresponds to the second position, and
• wherein the first CNN and the second CNN satisfy at least one condition in a first set of preset conditions that comprises:
• a network depth of the second CNN being greater than a network depth of the first CNN, a network width of the second CNN being greater than a network width of the first CNN, and a resolution of an input image of the second CNN being greater than a resolution of an input image of the first CNN.

A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors of an electronic device, cause the electronic device to be configured to:

• display a first shooting interface, wherein a first region of the first shooting interface displays a video stream shot by a camera lens;
• receive a first operation, when the first region displays an nth frame of image of the video stream, provided to the nth frame of image by a user, wherein n is a positive integer;
• perform feature extraction on the nth frame of image, in response to the first operation, to obtain a template feature, wherein the nth frame of image comprises a target;
• select a first tracking region from an (n+x)th frame of image of the video stream, wherein x is a positive integer;
• and
• search the first tracking region through a first convolutional neural network (CNN) based on the template feature, and output a first position and a first confidence that corresponds to the first position, wherein whether the (n+x)th frame of image comprises the target is based on the first confidence,
• wherein if the first confidence indicates that the (n+x)th frame of image does not comprise the target, the electronic device is further configured to search the first tracking region through a second CNN based on the template feature, and output a second position and a second confidence that corresponds to the second position, and
• wherein the first CNN and the second CNN satisfy at least one condition in a first set of preset conditions that comprises:
• a network depth of the second CNN being greater than a network depth of the first CNN, a network width of the second CNN being greater than a network width of the first CNN, and a resolution of an input image of the second CNN being greater than a resolution of an input image of the first CNN.