Weak and small figure target detection method based on scale matching

Abstract

The invention provides a weak and small figure target detection method based on scale matching. The method comprises the steps of migrating scale distribution of figures on a network pre-training dataset into scale distribution of weak and small figures on a target training set; when the target detection model is trained, obtaining the preliminary target detection model through pre-training on the pre-training data set after scale migration, and then obtaining the final target detection model through training on the target training set. According to the method, through scale matching, the model can better research and utilize information on a micro scale, so that the convolutional neural network or other models are more accurate in weak and small target representation, and the detection performance of a detector in the prior art is effectively improved.

Description

technical field [0001] The invention relates to the fields of computer vision and image processing, in particular to a scale-matching-based weak and small person target detection method. Background technique [0002] Pedestrian detection is an important topic in the field of computer vision and has a wide range of applications, including surveillance, driver assistance, mobile robotics, and rapid rescue at sea. With the rise of deep convolutional neural networks, unprecedented progress has been made in pedestrian detection, however, the detection of weak people is far from good results. Unlike objects of proper scale, the detection task of tiny objects is more challenging due to their very small relative and absolute sizes and low signal-to-noise ratio. If the video is from the image in the video, after the video encoding and decoding process, the blurred image will cause tiny objects to be mixed with the background, which makes it more difficult to obtain tiny targets. In...

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Problems solved by technology

[0005] For the weak and small person target detection problem we want to solve, there is currently no public external data set that can meet most of the standards for weak and small people (such as weak and small people with a scale of less than 20 pixels). Therefore, in the target data set and The problem of different scale distributions on the pre-training data set will become the main factor that limits the performance of the pre-training model on the data set.

[0006] The purpose of the present invention is to provide a simple and effective detection method for weak and small people to solve the above-mentioned problems in the detection of weak and small people, such as the lack of target data sets related to weak and small people, and the current public pre-training data sets are not suitable for weak and small people. The problem of limited performance improvement in detection

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