Difference between revisions of "Object Tracking and Anticipation"

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{{StudentProjectTemplate
 
{{StudentProjectTemplate
|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. 
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|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 deep learning-based tracking and anticipation algorithms work in scenes with falling snowflakes.  
 
|Prerequisites=A solid background in Python
 
|Prerequisites=A solid background in Python
 
and Machine Learning.
 
and Machine Learning.

Revision as of 12:05, 23 September 2024

Title Object Tracking and Anticipation
Summary String representation "The thesis pres … ing snowflakes." is too long.
Keywords
TimeFrame
References
Prerequisites A solid background in Python

and Machine Learning.

Author
Supervisor Eren Aksoy
Level Master
Status Open