The Research of the Real-time Detection and Recognition of Targets in Streetscape Videos
This addresses the problem of efficient target analysis in urban surveillance for applications like traffic monitoring, but it appears incremental as it builds on existing detection frameworks.
The study tackled real-time detection and recognition of targets in streetscape videos, achieving superior accuracy and robustness compared to conventional methods.
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.