Thema
Video Saliency Model Evaluation
Typ Master, Forschungspraxis, Bachelor, Ing.prax.
Betreuer Mikhail Startsev
Tel.: +49 (0)89 289-28550
E-Mail: mikhail.startsev@tum.de
Sachgebiet Human and Computer Vision
Beschreibung One of the important questions in computer vision is how you determine what information in a scene is relevant. So-called “saliency models” [1] have been used to predict informativeness in images [2] and videos. A quality ground truth labelling of the eye movements is what provides for an accurate and versatile evaluation of saliency models. This labelling is however, especially for video sequences, hard to come by.

Our group has been working on obtaining such ground truth data. And while this effort is still ongoing, evaluation of the existing saliency models can already begin. The candidate would explore the already available approaches to visual saliency prediction, with or without the provided source code, potentially modifying them and evaluating their results against the provided ground truth. As a result of this project we would get some insights into how our visual and attention systems work and can be better expressed.


Image source: jov.arvojournals.org/article.aspx

[1] en.wikipedia.org/wiki/Salience_(neuroscience)
[2] saliency.mit.edu/results_mit300.html
Voraussetzung Experience with machine learning concepts and programming skills are desirable.
Bewerbung If you are interested in this topic, we welcome the applications via the email address above. Please set the email subject to “<Type of application> application for topic 'XYZ'”, ex. “Master’s thesis application for topic 'XYZ'”, while clearly specifying why are you interested in the topic in the text of the message. Also make sure to attach your most recent CV (if you have one) and grade report.