In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
In this paper, we present a probabilistic formulation of kernel-based tracking methods based upon maximum likelihood estimation. To this end, we view the coordinates for the pixel...
Quang Anh Nguyen, Antonio Robles-Kelly, Chunhua Sh...
Two new techniques are proposed to improve stereo matching performance in this work. First, to address the disparity discontinuity problem in occluded regions, we present a dispar...
We present light fall-off stereo?LFS?a new method for computing depth from scenes beyond lambertian reflectance and texture. LFS takes a number of images from a stationary camera ...
In [8], the authors proposed the large deformation logunbiased diffeomorphic nonlinear image registration model which has been successfully used to obtain theoretically and intuit...
Igor Yanovsky, Paul M. Thompson, Stanley Osher, Lu...
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
This paper describes a patch-based approach for rapid image correlation or template matching. By representing a template image with an ensemble of patches, the method is robust wi...
We study retinal curvature estimation from multiple images that provides the fundamental geometry of human retina. We use an affine camera model due to its simplicity, linearity, ...
Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and t...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...