The Research of the Real-time Detection and Recognition of Targets in Streetscape Videos

TL;DR

This paper introduces a real-time target detection and recognition method for streetscape videos that leverages separation confidence and scale synthesis optimization, achieving high accuracy and robustness in high-definition, high-frame-rate scenarios.

Contribution

It presents a novel approach combining separation confidence computation with scale synthesis optimization for improved real-time detection and recognition in streetscape videos.

Findings

Superior accuracy over conventional methods

High robustness in diverse conditions

Effective in high-definition, high-frame-rate videos

Abstract

This study proposes a method for the real-time detection and recognition of targets in streetscape videos. The proposed method is based on separation confidence computation and scale synthesis optimization. We use the proposed method to detect and recognize targets in streetscape videos with high frame rates and high definition. Furthermore, we experimentally demonstrate that the accuracy and robustness of our proposed method are superior to those of conventional methods.