We present a novel approach to inferring 3D volumetric shape of both moving objects and static background from video sequences shot by a moving camera, with the assumption that th...
This paper presents a new shape registration algorithm that establishes "meaningful correspondence" between objects, in that it preserves the local shape correspondence ...
Yun Zhu, Xenophon Papademetris, Albert J. Sinusas,...
In the paper, we describe an optical system which is capable of providing external access to both the sensor and the lens aperture (i.e., projection center) of a conventional came...
Although it is usually assumed in many pattern recognition problems that different patterns are distinguishable, some patterns may have inseparable overlap. For example, some faci...
In this work we recover the 3D shape of mirroring objects such as mirrors, sunglasses, and stainless steel objects. A computer monitor displays several images of parallel stripes,...
Stas Rozenfeld, Ilan Shimshoni, Michael Lindenbaum
This paper advocates a Virtual Vision paradigm and demonstrates its usefulness in camera sensor network research. Virtual vision prescribes the use of a visually and behaviorally ...
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Registering consecutive images from an airborne sensor into a mosaic is an essential tool for image analysts. Strictly local methods tend to accumulate errors, resulting in distor...
In this work, we systematically study the problem of visual event recognition in unconstrained news video sequences. We adopt the discriminative kernel-based method for which vide...