Category
Computer Vision Deep Learning Image Processing
Scope
Two students completing a Masters Thesis (30 hp each).
Background
In the METS organization at Axis we develop a wide variety of products. These include thermal cameras and corresponding analytics solutions. A common use-case in analytics for surveillance is detection of objects such as people and vehicles. Modern approaches based on deep learning use large image datasets for training and testing of object detection models. However annotated datasets with thermal images are typically much smaller compared to their visual (RGB) counterparts. To leverage the existing large visual datasets for thermal object detection we would like to explore different techniques of translating visual images into thermal-looking ones. With the translated images available we want to evaluate the impact of using these for training thermal object detection models.
Goal
The goal of this thesis project is to evaluate the effectiveness of using thermal-looking images translated from visual (RGB) images for training thermal object detection models in the domain of surveillance. Specific objectives include:
Requirements
We are looking for students in the final stages of their Masters program with a strong interest in computer vision and machine learning. Experience with Python and deep learning frameworks like TensorFlow or PyTorch is essential.
OK I am interested! What do I do now
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Who to contact for any questions regarding the position!
Josefine Öder ()
Marcus Thelander Andrén ()
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