A tracking-based approach for video and volume annotation with - - PowerPoint PPT Presentation

A tracking-based approach for video and volume annotation with sparse point supervision

• L. Lejeune, J. Grossrieder, R. Sznitman

Ophthalmic Technology Laboratory, University of Bern, Switzerland

Problem

• Segmentation relies more and more on complex Machine Learning models
• Large amounts of ground truth annotations are necessary
• Annotating video/volumetric sequences is tedious

Ambitions

• Reduce user inputs to a

minimum

• No prior knowledge on the
• bject of interest
• Perform on a wide range of

datasets

Approach

• User provides a single 2D

location on the object of interest on each frame

• Leverage frame-to-frame

consistencies to propagate belief through a network

Advantages

• We can potentially annotate

at frame rate.

A tracking-based approach for video and volume annotation with sparse point supervision

• L. Lejeune, J. Grossrieder, R. Sznitman

Ophthalmic Technology Laboratory, University of Bern, Switzerland

Try it out at www.gazelabel.com