Master Thesis – Core Tech Graphics: Three Different Ideas

Dynamically updating a Digital Twin using monocular depth

• Develop a reliable approach for detecting and segmenting scene changes.
• Compare modern monocular depth-estimation models and select one suited to the project.
• Measure how accurately new objects can be placed in a Digital Twin, in terms of depth and position.
• Explore how cameras can help keep Digital Twins up to date without repeated rescanning.

Bring visual detail and thermal information together

Some cameras capture both a visual image, rich in color and detail, and a thermal image that reveals heat. Combining the two views can provide more useful information, but differences in field of view and the way objects appear can make alignment challenging.

• Review research on automatic alignment of visual and thermal images.
• Implement or adapt methods for detecting shared features in paired images, then compare their performance.
• Identify the conditions that help or hinder alignment.
• Assess what data, calibration, or further development would be needed for a practical solution.
• Present a demonstration, findings, and recommendations for future work.

Towards more accurate 3D indoor reconstruction

Body-worn cameras record rooms, corridors, and objects as the wearer moves through a building. This footage could help create 3D indoor reconstructions, but camera movement, changing viewpoints, and occlusions make it difficult to understand the scene accurately.

• Improve depth estimation and segmentation in body-worn camera footage.
• Establish a baseline using pre-trained V-JEPA features and task-specific prediction modules.
• Test improvements to training objectives and ways of combining features from different model layers.
• Explore whether information across video frames can make predictions more consistent.
• Evaluate depth and segmentation results, then assess their effect on indoor reconstruction using an existing 3D pipeline.

This cross-team project at Axis brings together practical programming and research in video world models and 3D computer vision. It’s an opportunity to apply emerging AI techniques to a real-world challenge.

Sara Garmark, hiring manager

+46 46 287 97 77

Certain roles at Axis require background checks, which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.

We enable a smarter and safer world by creating innovative solutions for improving security and business performance. As a network technology company and industry leader, we offer solutions in video surveillance, access control, intercom, and audio systems, enhanced by intelligent analytics applications.

With around 6,000 committed employees in over 50 countries, we collaborate with partners worldwide. Together, we thrive in our friendly, open, and collaborative culture and inspire each other to think beyond the expected. United by our commitment to inclusion, diversity, and sustainability, we consistently seek to develop our skills and way of working.

For more information about Axis, please visit our website www.axis.com.

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