Multi-target tracking detection method and device based on Darkflow-DeepSort and storage medium

A technology of tracking detection and target detection, which is applied in image data processing, instruments, character and pattern recognition, etc., to achieve the effects of easy transplantation, reduced ID jumps, and fast processing speed

Pending Publication Date: 2019-11-29
PING AN TECH (SHENZHEN) CO LTD
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However, when using this method of DeepSort tracking, the maximum fps can reach about 15fps, but

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  • Multi-target tracking detection method and device based on Darkflow-DeepSort and storage medium
  • Multi-target tracking detection method and device based on Darkflow-DeepSort and storage medium
  • Multi-target tracking detection method and device based on Darkflow-DeepSort and storage medium

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[0044] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that these embodiments may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing one or more embodiments.

[0045] The invention provides a multi-target tracking and detection method based on Darkflow-DeepSort, an electronic device and a storage medium. Among them, the multi-target tracking and detection method based on Darkflow-DeepSort includes the target detection stage and the target tracking stage; it involves two models, Darkflow and DeepSort, among which the Darkflow model is mainly used for training samples for pedestrian detection, and the DeepSort model only uses the tracking part such as Kalman filter confirms trajectories, etc. The multi-target tracki...

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Abstract

The invention provides a multi-target tracking detection method and device based on Darkflow-DeepSort, and a storage medium, and relates to the technical field of intelligent decision making. The multi-target tracking detection method comprises the following steps: S110, carrying out the training through employing a YOLOv3 algorithm, and obtaining a Darkflow-based target detection model; S120, inputting the detection image into a trained Darkflow-based target detection model to obtain apparent characteristics of a plurality of targets, wherein the detection image is obtained by decoding a monitoring video; S130, inputting the apparent characteristics of the plurality of targets into a trained DeepSort-based target tracking model, wherein the target tracking model is obtained by training adata set MOT16Challenge of multi-target detection; and S140, performing frame-by-frame data association processing on the monitoring video by using a Kalman filter of a target tracking model to realize multi-target tracking in the monitoring video. By utilizing the multi-target tracking detection method, the multi-target tracking detection speed can be increased, and multi-target tracking is completed under the condition that the detection accuracy is not lost.

Description

technical field [0001] The present invention relates to the technical field of intelligent decision-making, and more specifically, to a method, device and storage medium for multi-target tracking and detection based on Darkflow-DeepSort. Background technique [0002] The method of visual target tracking is widely used in human-computer interaction, unmanned driving and other fields. The tracking method based on correlation filter (Correlation Filter) and convolutional neural network (CNN) has occupied more than half of the target tracking field. [0003] Among the existing multi-target tracking methods, the SORT method (SIMPLE ONLINE AND REALTIME TRACKING, simple online and real-time tracking) has achieved better results. The biggest feature of this method is that it efficiently realizes target detection and uses Kalman filter to filter and Hungarian algorithm for tracking. [0004] DeepSort is an improvement on the basis of SORT target tracking. It uses the original DeepSo...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/277
CPCG06T7/277G06T2207/10016G06T2207/20081G06T2207/20084G06V20/42G06V2201/07
Inventor 王义文郑权王健宗曹靖康
Owner PING AN TECH (SHENZHEN) CO LTD
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