CVJul 6, 2022

Multi-area Target Individual Detection with Free Drawing on Video

arXiv:2207.02467v13 citationsh-index: 3
AI Analysis

This is an incremental improvement for video monitoring and detection applications, enabling customizable, real-time multi-area detection with a model-independent approach.

This paper tackles the problem of real-time detection in multiple custom-drawn areas on video by introducing a design that allows free drawing of detection zones with polylines and color-coded outlines, achieving real-time efficiency using tools like PIL, OpenCV, and Tkinter.

This paper has provided a novel design idea and some implementation methods to make a real time detection of multi-areas with multiple detecting areas that are generated by the real time drawing on the screen display of the video. The drawing on the video will remain the output as polylines, and the colors of the outlines will change when the stage of drawing or detecting is changed. The shape of the drawn area is free to be customized and real-time effective. The configuration of the drawn areas can be renewed and the detecting areas are working individually. The detection result should be shown with a GUI designed by Tkinter. The object recognition model was developed on YOLOv5 but can be changed to others, which means the core design and implementation idea of this paper is model-independent. With PIL and OpenCV and Tkinter, the drawing effect is real time and efficient. The design and code of this research is basic and can be extended to be implemented in numerous monitoring and detecting situations.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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