Model training method and device, terminal and storage medium

Abstract

The embodiment of the invention discloses a model training method and device, a terminal and a storage medium. The method comprises: acquiring a template image and a test image; calling the first object recognition model to process the characteristics of the tracking object in the template image to obtain a first reference response, and calling the second object recognition model to process the characteristics of the tracking object in the template image to obtain a first reference response; calling the first object recognition model to process the characteristics of the tracking object in thetest image to obtain a first test response, and calling the second object recognition model to process the characteristics of the tracking object in the test image to obtain a second test response; tracking the first test response to obtain a tracking response of the tracked object; and updating the first object recognition model based on the difference information between the first reference response and the second reference response, the difference information between the first test response and the second test response and the difference information between the tracking tag and the tracking response. According to the embodiment of the invention, the accuracy of visual target tracking can be improved.

Description

technical field [0001] The present invention relates to the field of Internet technology, in particular to the field of visual object tracking, and in particular to a model training method, a model training device, a terminal and a storage medium. Background technique [0002] With the development of science and technology, computer vision has become a popular research field, and visual object tracking is an important research direction in the field of computer vision. The so-called visual object tracking refers to predicting the size and position of the tracking object in other images when the size and position of the tracking object in a certain image are known. Visual object tracking is usually used in video surveillance, human-computer interaction, and unmanned driving and other application scenarios that require high real-time performance. For example, the size and position of the tracking object in a certain frame image in a given video sequence In this case, predict ...

AI Technical Summary

Problems solved by technology

At present, visual target tracking is mainly implemented by using traditional image processing models, but the inventors have found in practice that traditional image processing models are designed to achieve image classification tasks and are trained using image classification data. However, Visual object tracking is not for image classification tasks, so traditional image processing models are not suitable for application in visual object tracking scenarios, resulting in low accuracy of visual object tracking

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