Object Tracking and Anticipation
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| Title | Object Tracking and Anticipation |
|---|---|
| Summary | The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. The student will analyze how different tracking and anticipation algorithms in scenes with falling snowflakes. Given the detected object bounding boxes, the student will experiment with Kalman Filtering, Extended Kalman Filtering, Particle Filtering, and Deep Learning-based tracking methods. As a dataset, the student will use CADC together with a custom object detection method. The thesis will be carried out as part of an EU project ROADVIEW. |
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| Prerequisites | A solid background in Python
and Machine Learning. |
| Author | |
| Supervisor | Eren Aksoy |
| Level | Master |
| Status | Open |
