Single target tracking method based on convolution neural network
A convolutional neural network and single-target technology, which is applied in the field of computer vision tracking, can solve problems such as illumination changes, occlusions, and deformations that are not robust, and achieve the effects of improving robustness, accuracy, and accuracy
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Problems solved by technology
 The present invention will be further described below in combination with specific embodiments.
 (1) Construct and train the network model
 This method uses the labeled data set to pre-train a network model offline. The function of the network model is to extract and match the features of each candidate area input into the network, and calculate the score of each candidate area, so as to distinguish the input Which of the candidate regions are target objects and which are not. Then in the actual tracking test, first use the current tracking video information to fine-tune the network online, so that it can achieve the effect of being able to well adapt to tracking the current target.
 Step 1: First, prepare the data set to be used for offline pre-training of the network model. The test data set of this method is the OTB50 data set, and the training data set is the VOT data set. OTB is a standard tracking benchmark data set, which contains 50 ful...
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