An Object Tracking Method Based on Triple Siamese Hash Network Learning

Abstract

The invention discloses a target tracking method based on triple twin hash network learning, and relates to the technical fields of computer vision, target tracking and deep learning. The method first constructs a triple twin hash network, which consists of three parts: data input layer, convolutional feature extraction layer, and hash coding layer. In the initial training process of the network, the triple twin hash network is trained using the training data set and the stochastic gradient descent backpropagation algorithm. After the training is completed, the network can obtain the initial ability of target positioning. In the tracking process, the input image is first passed through the triple-twin region recommendation network to obtain the corresponding candidate frame, and then the candidate frame is input into the triple-twin hash network for forward processing, and the similarity between each candidate frame and the query sample is calculated separately, and the highest candidate frame is selected. The candidate boxes of similarity are used as tracking target objects to achieve target tracking.

Description

technical field [0001] The invention relates to the technical fields of computer vision, target tracking and deep learning. Background technique [0002] Target tracking is a very popular research topic in the field of computer vision. Its research content is to automatically identify the target object to be tracked in the subsequent video sequence according to a given video clip, and obtain the continuous position, appearance and motion of the target. . Target tracking is widely used in military and civilian intelligent monitoring, human-computer interaction, traffic monitoring and other fields, and has strong practical value. Although this research topic has been studied for decades, it remains a challenging one. In real-world situations, target objects are easily disturbed by various factors, such as illumination changes, pose changes, target occlusion, etc., making developing a consistently robust target tracking system a very challenging problem. [0003] Over the pa...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a target tracking method based on triple twin hash network learning, which can effectively solve the problems of large memory space and large amount of parameter calculation caused by traditional deep learning directly using fully connected layer calculations. question

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