Siyuan’s Algorithm on Multi-object Tracking Ranked Top in the UA-DETRAC Dataset Tracking Challenge

A multi-object tracking algorithm developed by Siyuan Chen is ranked top in the tracking task leaderboard of the UA-DETRAC dataset. UA-DETRAC is a challenging real-world multi-object detection and multi-object tracking benchmark. The dataset consists of 10 hours of videos captured with a Cannon EOS 550D camera at 24 different locations at Beijing and Tianjin in China. The videos are recorded at 25 frames per seconds (fps), with the resolution of 960×540 pixels. There are more than 140 thousand frames in the UA-DETRAC dataset and 8250 vehicles that are manually annotated, leading to a total of 1.21 million labeled bounding boxes of objects.

Read more details about the dataset and the algorithm here.