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Updated: Jun 30, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

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A real-time arbitrary-shape text detector.

Manhuai Lu¹, Langlang Li², Chin-Ling Chen^3,4

¹College of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, China.

|April 16, 2024

Summary

This summary is machine-generated.

This study introduces a real-time arbitrary-shape text detection system using YOLOv6. The novel approach enhances accuracy and speed for text detection in natural scenes.

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Area of Science:

Computer Vision
Artificial Intelligence
Image Processing

Background:

Detecting arbitrary-shape text in natural scenes presents significant challenges.
Existing methods often lack real-time capabilities or practical applicability.

Purpose of the Study:

To develop an effective and real-time detector for arbitrary-shape text.
To improve upon current limitations in arbitrary-shape text detection.

Main Methods:

A YOLOv6-based architecture was adapted for text detection.
Two additional branches were integrated into the YOLOv6 neck.
The pixel aggregation (PA) algorithm was utilized for the detection head.

Main Results:

The proposed method achieved high detection accuracy and real-time performance.
On Total-Text (640x640), an F-measure of 84.1% at 291.8 FPS was recorded.
On ICDAR2015 (896x896), an F-measure of 81.5% at 199.6 FPS was achieved.

Conclusions:

The YOLOv6-based detector effectively addresses arbitrary-shape text detection challenges.
The method demonstrates superior performance in both accuracy and speed compared to existing approaches.