Jog, GM and Fathi, H and Brilakis, I (2011) Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications. Advanced Engineering Informatics, 25. pp. 725-735. ISSN 1474-0346Full text not available from this repository.
Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.
|Uncontrolled Keywords:||Fundamental matrix Speeded Up Robust Features (SURF) Normalized eight-point algorithm|
|Depositing User:||Cron job|
|Date Deposited:||16 Jul 2015 13:31|
|Last Modified:||31 Jul 2015 03:30|