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[AAAI 2024] UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation. UCMCTrack achieves SOTA on MOT17 using estimated camera parameters.
| Date | Stars |
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| 2026-07-24 | 372 |
| 2026-07-25 | 372 |
| 2026-07-28 | 372 |
| 2026-07-30 | 372 |
| 2026-08-06 | 372 |
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# UCMCTrack > **[AAAI 2024] UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation**. > UCMCTrack is a simple pure motion based tracker that achieves state-of-the-art performance on multiple datasets. In particular, **it achieves the first place on MOT17 without using any appearance cues**, making it highly applicable for real-time object tracking on end devices. [](https://arxiv.org/abs/2312.08952) [](https://paperswithcode.com/sota/multi-object-tracking-on-mot17?p=ucmctrack-multi-object-tracking-with-uniform) [](https://paperswithcode.com/sota/multi-object-tracking-on-mot20-1?p=ucmctrack-multi-object-tracking-with-uniform) ## 🚗 Tracking Vehicles with Moving Camera  ## 📷 Estimating Camera Parameter from a Single Image  ## 📰 News * [12/29/2023] **Open-Sourcing a Tool for Estimating Camera Parameters from a Single Image！** For specific steps, refer to Get Started. * [01/02/2024] **Usage Guide Now Available for the Camera Parameter Estimation Tool!** * [01/02/2024] **Add head padding (HP) post-processing trick as OC-SORT.** Now the performance gap between the Python version of the code and the C++ version in the paper has been eliminated. ## 📈 Star Rising [](https://star-history.com/#corfyi/UCMCTrack&Timeline) ## ⭐ Stargazers [](https://github.com/corfyi/UCMCTrack/stargazers) [](https://hits.seeyoufarm.com) ## 🚩 Demo This demo demonstrates the use of YOLOv8x as the detector and UCMCTrack as the tracker for real-time vehicle detection and tracking from a video file. The demo processes the video file `demo.mp4` to detect and track vehicles, saving the tracking results in the `output` folder. **In the case of significant camera shake**, UCMCTrack still has good performance without using any appearance information. #### Environment Before you begin, ensure you have the following prerequisites installed on your system: - Python (3.8 or later) - PyTorch with CUDA support - Ultralytics Library - Download weight file [yolov8x.pt](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x.pt) to folder `pretrained` #### Run the demo ```bash python demo.py --cam_para demo/cam_para.txt --video demo/demo.mp4 ``` The file `demo/cam_para.txt` is the camera parameters estimated from a single image. The code of this tool is released. For specific steps, please refer to the Get Started. ## 🗼 Pipeline of UCMCTrack First, the detection boxes are mapped onto the ground plane using homography transformation. Subsequently, the Correlated Measurement Distribution (CMD) of the target is computed. This distribution is then fed into a Kalman filter equipped with the Constant Velocity (CV) motion model and Process Noise Compensation (PNC). Next, the mapped measurement and the predicted track state are utilized as inputs to compute the Mapped Mahalanobis Distance (MMD). Finally, the Hungarian algorithm is applied to associate the mapped measurements with tracklets, thereby obtaining complete tracklets.  ## 🖼️ Visualization of Different Distances (a) Visualization of IoU on the image plane. IoU fails as there is no intersection between bounding boxes. (b) Visualization of Mapped Mahalanobis D
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matched fp:6220bbecd39d2ec9, topic:computer-vision, topic:object-tracking, desc:object tracking