In this review of estimation problems in restricted parameter spaces, we focus through a
series of illustrations on a number of methods that have proven to be successful. These …

A new signal detection and estimation method based on the intermittency transition between
order and chaos is developed. The corresponding bifurcation process for the Duffing …

An important objective in the evaluation of algorithms with sensory inputs is the development
of measures characterizing the intrinsic errors in the results. Intrinsic are those errors which …

Deformable models are a useful modeling paradigm in computer vision. A deformable
model is a curve, a surface, or a volume, whose shape, position, and orientation are …

We study confidence sets for a parameter θ∈ Θ that have minimax expected measure
among random sets with at least 1-α coverage probability. We characterize the minimax sets …

We describe an estimation technique which, given a measurement of the depth of a target
from a wide-field-of-view (WFOV) stereo camera pair, produces a minimax risk fixed-size …

We characterize the precision of a 3-D reconstruction from stereo: we derive confidence
intervals for the components (X, Y, Z) of the reconstructed 3-D points. The precision …

We present results confirming the importance of radiometric correction in multicamera
applications. Although, we compensate for systematic noise only, we review all noise …

The purpose of this paper is to introduce the reader to a novel approach to data fusion. We
focus on the latest results which have immediate practical implications. Many tasks in active …

In this paper we describe a statistical method for the integration of an unlimited number of
cues within a deformable model framework. We treat each cue as a random variable, each …