Epipolar geometry is a key point in computer vision and the fundamental matrix estimation is the only way to compute it. This article is a fresh look in the subject that overview classic and …
A Rosenfeld - Computer vision and image understanding, 1999 - Elsevier
This paper presents a bibliography of over 2250 references related to computer vision and image analysis, arranged by subject matter. The topics covered include computational …
In order to monitor sufficiently large areas of interest for surveillance or any event detection, we need to look beyond stationary cameras and employ an automatically configurable …
I Koufakis, BF Buxton - Image and Vision computing, 1999 - Elsevier
We present an image synthesis technique for very low bit rate encoding of faces for videoconferencing applications over the Internet or mobile communication networks. The …
A theoretical framework is presented to study the consistency of robust estimators used in vision problems involving extraction of fine details. A strong correlation between asymptotic …
K Kanatani - Proc. 6th Symp. Sensing via Image Inf, 2000 - Citeseer
This paper presents an optimal linear algorithm for computing the fundamental matrix from corresponding points over two images under an assumed model, which admits independent …
M Yang, Y Liu, Z You - Neurocomputing, 2011 - Elsevier
The epipolar geometry is the intrinsic projective geometry between two views, and the algebraic representation of it is the fundamental matrix. Estimating the fundamental matrix …
K Kanatani, N Ohta - Journal of Electronic Imaging, 2003 - spiedigitallibrary.org
We present two linear algorithms for 3-D reconstruction: one is for finite motion; the other is for optical flow. We compare their performance by simulation and real-image experiments …
In applications such as video mosaicing, foreground/background separation and camera pose estimation, feature correspondences are the fundamental building blocks upon which …