In object tracking, change of object aspect is a cause of failure due to significant changes of object appearances. The paper proposes an approach to this problem without a priori ...
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
We present an algorithm for color classification with explicit illuminant estimation and compensation. A Gaussian classifier is trained with color samples from just one training im...
Abstract. For shapes represented as closed planar contours, we introduce a class of functionals that are invariant with respect to the Euclidean and similarity group, obtained by p...
Siddharth Manay, Byung-Woo Hong, Anthony J. Yezzi,...
We address the fundamental problem of matching in two static images. The remaining challenges are related to occlusion and lack of texture. Our approach addresses these difficultie...
We analyze visibility from static sensors in a dynamic scene with moving obstacles (people). Such analysis is considered in a probabilistic sense in the context of multiple sensors...
Abstract. Complete 3-D modeling of a free-form object requires acquisition from multiple view-points. These views are then required to be registered in a common coordinate system b...
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...
Abstract. A novel algorithm is presented for the 3D reconstruction of human action in long (> 30 second) monocular image sequences.A sequence is represented by a small set of au...
Gareth Loy, Martin Eriksson, Josephine Sullivan, S...
We present a method for estimating intrinsic images from a fixed-viewpoint image sequence captured under changing illumination directions. Previous work on this problem reduces the...
Yasuyuki Matsushita, Stephen Lin, Sing Bing Kang, ...