| Paper: | WP-L5.4 |
| Session: | Motion Detection and Estimation III |
| Time: | Wednesday, September 19, 15:30 - 15:50 |
| Presentation: |
Lecture
|
| Title: |
A MULTI-LAYER MRF MODEL FOR OBJECT-MOTION DETECTION IN UNREGISTERED AIRBORNE IMAGE-PAIRS |
| Authors: |
Csaba Benedek; Pázmány Péter Catholic University | | |
| | Tamás Szirányi; Computer and Automation Research Institute | | |
| | Zoltan Kato; University of Szeged | | |
| | Josiane Zerubia; INRIA Sophia Antipolis | | |
| Abstract: |
In this paper, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse matching instead of a precise image registration. The challenge of the proposed model is to eliminate the registration errors, noise and the parallax artifacts caused by the static objects having considerable height (buildings, trees, walls etc.) from the difference image. We describe the background membership of a given image point through two different features, and introduce a novel three-layer Markov Random Field (MRF) model to ensure connected homogenous regions in the segmented image. |
