We present a real-time approach for image-based localization within large scenes that have been reconstructed offline using structure from motion (Sfm). From monocular video, our...
Hyon Lim, Sudipta N. Sinha, Michael F. Cohen, Matt...
: The SIFT algorithm (Scale Invariant Feature Transform) proposed by Lowe [1] is an approach for extracting distinctive invariant features from images. It has been successfully app...
Abstract. We introduce a view–point invariant representation of moving object trajectories that can be used in video database applications. It is assumed that trajectories lie on...
In this paper, we developed a family of 2D and 3D invariant features with applications to 3D human faces recognition. The main contributions of this paper are: (a) systematically ...
Abstract: Some surfaces, like metallic and varnished ones, can only be properly controlled, if they are inspected under different illumination directions. This requires a three-dim...
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Due to the increasing amount of 3D data for various applications there is a growing need for classification and search in such databases. As the representation of 3D objects is no...
In this paper we propose an image retrieval scheme based on projectively invariant features. Since cross-ratio is the fundamental invariant feature under projective transformation...
S. Rajashekhar, Subhasis Chaudhuri, Vinay P. Nambo...
`Invariant regions' are image patches that automatically deform with changing viewpoint as to keep on covering identical physical parts of a scene. Such regions are then desc...
Invariant features or operators are often used to shield the recognition process from the effect of "nuisance" parameters, such as rotations, foreshortening, or illumina...