Automatic ship tracking method and system based on deep learning network and mean shift

Abstract

The invention relates to an automatic ship tracking method and system based on a deep learning network and mean shift. The method comprises the steps that monitoring video data including coastal areamonitoring video data under visible light are acquired, and each frame of image is extracted; preprocessing is carried out to extract the positive sample and negative sample of a ship target; throughan area-based convolutional neural network method, the samples of the ship target in a video are input into a neural network for model training; the initial frame data of the video are extracted, andship detection and probability density calculation are carried out on initial moment data according to a trained model; and the ship tracking result at the current moment is determined through the calculation result of the previous moment. According to the invention, the method has a great detection result for complex scenes such as clouds, cloudy days, rain and the like; the method has the advantages of high robustness and stability and fully automated tracking process; the stability and accuracy of the neural network method eliminate errors for a mean shift method; and a basis is laid for the tracking of an emerging target.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, in particular to an automatic ship tracking method based on a deep learning network and mean shift. Background technique [0002] In today's society, video surveillance cameras are ubiquitous. If we only rely on human eye observation and detection, it is easy to miss abnormal events in the video. With the rapid development of computer network, communication and semiconductor technology, people are more and more favored to use computer vision instead of human eyes to analyze the video image obtained by the sensor and obtain useful information in the image. Video tracking is a focus of computer vision research, it is mainly to track the target of interest obtained by the image sensor. Video tracking is the basis of many video applications, such as traffic monitoring, intelligent robots, and human-computer interaction. It plays an important role in smart city management, combating ...

AI Technical Summary

Problems solved by technology

The offline learning method is less effective for dynamically changing target tracking, while the online learning method is prone to error accumulation due to the introduction of new errors for each update, and eventually drifts or even loses the target.

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