We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
A key problem in widely distributed camera networks is geolocating the cameras. This paper considers three scenarios for camera localization: localizing a camera in an unknown env...
Nathan Jacobs, Scott Satkin, Nathaniel Roman, Robe...
This paper develops an algorithm for estimating the epipole or direction of translation of a moving monocular observer. To this end, we use constraints arising from two points tha...
The photorealistic modeling of large-scale objects, such as urban scenes, requires the combination of range sensing technology and digital photography. In this paper, we attack th...
Boosting is a remarkably simple and flexible classification algorithm with widespread applications in computer vision. However, the application of boosting to nonEuclidean, infini...
This paper addresses the problem of video inpainting, that is seamlessly reconstructing missing portions in a set of video frames. We propose to solve this problem proceeding as f...
We consider the problem of estimating the relative orientation of a number of individual photocells -or pixels- that hold fixed relative positions. The photocells measure the inte...
Epipolar geometry and relative camera pose computation for uncalibrated cameras with radial distortion has recently been formulated as a minimal problem and successfully solved in...
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
An approach for incremental learning of a 3D scene from a single static video camera is presented in this paper. In particular, we exploit the presence of casual people walking in...
Diego Rother, Kedar A. Patwardhan, Guillermo Sapir...