Multiclass object detection in aerial and satellite images - diploma a német DLR Aerospace kutatóintézetnél

Tanszéki konzulens: 
A munkatárs fényképe
tanszékvezető, egyetemi tanár
Szoba: IE442
Tel.:
+36 1 463-2065
Email: daboczi (*) mit * bme * hu
Külső konzulens: 
Máttyus Gellért, DLR Aerospace

A kiírás adatai

A téma státusza: 
Korábbi (jelenleg nem aktív, de látszik)
Kiírás éve: 
2013
A kiírás jellege: 
szakdolgozat/diplomaterv

Multiclass object detection in aerial and satellite images

(For Computer Science, Electrical Engineering, Informatics Students)

Your mission:

The Photogrammetry and Image Analysis department of the DLR has developed a system for monitoring the road traffic from aerial images in real-time (the project VABENE: vabene.dlr.de) and a system for monitoring ships from optical satellite images in near real-time (the project OpsServe). In both systems a crucial part is a reliable and fast visual object detector. In the next phases of the projects the existing detector needs to be extended for multiple object classes.

The proposed master thesis focuses on developing a visual object detector which detects multiple object types (e.g. vehicles, ships) on aerial and satellite images.

The main tasks are:

  • Studying the state of the art computer vision methods for object detection and classification
  • Implementing the detector C++ program using the openCV computer vision library
  • Evaluating the performance of the detector.

Your qualifications:

  • student in computer science, electrical engineering, informatics or comparable studies
  • intermediate English for reading and understanding the literature
  • experience in at least one of the topics signal processing, image processing, computer vision, machine learning
  • good programming skills, experience in object oriented programming (C++ preferred)

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment.

Course paper / final thesis

immediately

 

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