The goal of this research is to develop the prototype of a tactile sensing platform for anthropomorphic manipulation research. We investigate this problem through the fabrication and simple control of a planar 2-DOF robotic ...

Parallel shared-memory machines with hundreds or thousands of processor-memory nodes have been built; in the future we will see machines with millions or even billions of nodes. Associated with such large systems is a new ...

The HMAX model has recently been proposed by Riesenhuber & Poggio as a hierarchical model of position- and size-invariant object recognition in visual cortex. It has also turned out to model successfully a number of ...

The ability to detect faces in images is of critical ecological significance. It is a pre-requisite for other important face perception tasks such as person identification, gender classification and affect analysis. Here ...

In this thesis I will be concerned with linking the observed speechsignal to the configuration of articulators.Due to the potentially rapid motion of the articulators, the speechsignal can be highly non-stationary. The ...

We describe a new direct method for estimating structure and motion from image intensities of multiple views. We extend the direct methods of Horn- and-Weldon to three views. Adding the third view enables us to solve ...

Novel algorithms for object recognition are described that directly recover the transformations relating the image to its model. Unlike methods fitting the typical conventional framework, these new methods do not ...

The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots. We introduce an approach for estimating the walking direction of people ...

The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots.We introduce an approach for estimating the walking direction of people ...

We present a framework for learning abstract relational knowledge with the aimof explaining how people acquire intuitive theories of physical, biological, orsocial systems. Our approach is based on a generative relational ...

Given a set of images containing multiple object categories,we seek to discover those categories and their image locations withoutsupervision. We achieve this using generative modelsfrom the statistical text literature: ...

A fundamental question in visual neuroscience is how to represent image structure. The most common representational schemes rely on differential operators that compare adjacent image regions. While well-suited to encoding ...

A fundamental question in visual neuroscience is how to represent image structure. The most common representational schemes rely on differential operators that compare adjacent image regions. While well-suited to encoding ...

In this paper, we discuss a wireless grid in which users are highly mobile, and form ad-hoc and sometimes short-lived connections with other devices. As they roam through networks, the users may choose to employ ...

Freehand sketching is a natural and crucial part of everyday humaninteraction, yet is almost totally unsupported by current user interfaces. With the increasing availability of tablet notebooks and pen based PDAs, sketchbased ...

In this paper, we present a static image compression algorithm for very low bit rate applications. The algorithm reduces spatial redundancy present in images by extracting and encoding edge and mean information. Since ...

Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature sets' similarity via a voting scheme (which ...

This paper presents an approach to model selection for regularized least-squares on reproducing kernel Hilbert spaces in the semi-supervised setting. The role of effective dimension was recently shown to be crucial in the ...

In this paper we describe a technique of classifier combination used in a human identification system. The system integrates all available features from multi-modal sources within a Bayesian framework. The framework allows ...

This paper presents a novel algorithm for learning in a class of stochastic Markov decision processes (MDPs) with continuous state and action spaces that trades speed for accuracy. A transform of the stochastic MDP ...