Unsupervised Clustering of Public Transport Vehicles Using Deep Morphological Features and Color Histograms
Surveillance cameras along urban roads produce large volumes of unlabeled video that could support the monitoring of public transport, but grouping the observed vehicles into meaningful categories without manual annotation remains challenging, since buses from different routes often share the same body structure and differ mainly in their color schemes. This study presents an unsupervised clustering methodology for public transport vehicles that combines morphological features extracted with a frozen DINOv2 Vision Transformer and handcrafted HSV color histograms through weighted early fusion, followed by UMAP projection and K-Means clustering. The method was evaluated on 7,972 bus images ...
| Authors | Juan Irving Vasquez |
|---|---|
| Primary category | cs.CV |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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