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Research on Real-time Detection and Tracking Algorithm for Low Slow Small Targets Based on the DeepSort

Published: 29 May 2024 Publication History

Abstract

Aiming at the problems of large tracking errors and high loss detection rates in existing algorithms for detecting and tracking low slow small targets such as drones, an improved online low slow small target detection and tracking algorithm based on YOLOv5 and DeepSort is proposed. Firstly, the collected degraded image is processed to enhance the feature information of small targets; the YOLOv5 algorithm is used to detect the target, and the target motion model is established after initializing the Kalman filter. The target appearance model is established based on the appearance characteristics of the target detection results; the DeepSort algorithm associates the new detection result with the existing trajectory based on the data obtained from the appearance model and the motion model and performs the association measurement through the Hungarian algorithm to complete the matching of the trajectory and detection. At the same time, when detecting and tracking in the next frame, the ROI is set to improve the detection efficiency and tracking stability of small targets to achieve real-time detection and tracking of the low slow small target. The experimental result on the self-built dataset shows that the photoelectric equipment using this method can detect and track low slow small targets effectively.

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cover image ACM Other conferences
CACML '24: Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning
March 2024
478 pages
ISBN:9798400716416
DOI:10.1145/3654823
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 29 May 2024

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Author Tags

  1. DeepSort
  2. Detection
  3. Low slow small targets
  4. Tracing
  5. YOLOv5

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CACML 2024

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Overall Acceptance Rate 93 of 241 submissions, 39%

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