We present the theory behind a novel unsupervised method for discovering quasi-static objects, objects that are stationary during some interval of observation, within image sequen...
Brandon C. S. Sanders, Randal C. Nelson, Rahul Suk...
In this paper, we address the problem of semisupervision in the framework of parametric clustering by using labeled and unlabeled data together. Clustering algorithms can take adv...
We provide elementary geometric arguments to show that the principal point of cameras with small to moderate field of view cannot be reliably estimated from natural, noisy images ...
This paper proposes a novel method for the projective reconstruction of planes and cameras from multiple images by factorizing a matrix containing all planar homographies between ...
This paper presents and compares 3 methods for the statistical localization of partially occulted landmarks. In many real applications, some information is visible in images and s...
Barbara Romaniuk, Michel Desvignes, Marinette Reve...
We present a fast non-iterative method for approximating the leading eigenvector so as to render graph-spectral based grouping algorithms more efficient. The approximation is base...
Antonio Robles-Kelly, Sudeep Sarkar, Edwin R. Hanc...