(12.35 MB) Abstract
Advisors: Mathias Lux (Klagenfurt University) and Xavier Giró-i-Nieto (UPC)
Degree: Electronic Engineering (5 years) at Telecom BCN-ETSETB (UPC)
Grade: A (9.5/10)
This project explores the potential of LIRE, an en existing Content-Based Image Retrieval (CBIR) system, when used to retrieve medical videos. These videos are recording of the live streams used by surgeons during the endoscopic procedures, captured from inside of the subject. The growth of such video content stored in servers requires search engines capable to assist surgeons in their management and retrieval. In our tool, queries are formulated by visual examples and those allow surgeons to re-find shots taken during the procedure. This thesis presents an extension and adaptation of Lire for video retrieval based on visual features and late fusion. The results are assessed from two perspectives: a quantitative and qualitative one. While the quantitative one follows the standard practices and metrics for video retrieval, the qualitative assessment has been based on an empirical social study using a semi-interactive web-interface. In particular, a thinking aloud test was applied to analyze if the user expectations and requirements were fulfilled. Due to the scarcity of surgeons available for the qualitative tests, a second domain was also addressed: videos captured at musical performances. These type of videos has also experienced an exponential growth with the advent of affordable multimedia smart phones, available to a large audience. Analogously to the endoscopic videos, searching in a large data set of such videos is a challenging topic.
