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About this paper
Muhammad Imran Zaman, Usama Ijaz Bajwa, Gulshan Saleem, Rana Hammad Raza
A multi-object multi-camera tracking framework combines Mask R-CNN detection, ResNet-152 feature extraction, and Deep SORT tracking to enable city-scale traffic monitoring, achieving an IDF1 score of 0.8289 and precision of 0.9026 on the 5th AI City Challenge dataset while handling challenges like occlusions and varying lighting conditions.
Key insights
- Separate deep visual feature generation process for Deep SORT significantly reduces training time
- Transfer learning and carefully selected loss functions help handle real-world challenges like occlusion and illumination variations
- Combining multiple state-of-the-art models enables robust performance across different camera views
Summary by alphaXiv.
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