Results 11 - 20 of 6,836

Model-based three-dimensional interpretations of two-dimensional images

by Rodney A. Brooks - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1983
"... ACRONYM IS a comprehensive domain independent modelbased system for vision and manipulation related tasks. Many of its sub-modules and representations have been described elsewhere. Here the derivation and use of invariants for image feature prediction is described. We describe how predictions of im ..."
Abstract - Cited by 109 (0 self) - Add to MetaCart
ACRONYM IS a comprehensive domain independent modelbased system for vision and manipulation related tasks. Many of its sub-modules and representations have been described elsewhere. Here the derivation and use of invariants for image feature prediction is described. We describe how predictions

Psychophysiological and Modulatory Interactions in Neuroimaging

by K. J. Friston, C. Buechel, G. R. Fink, J. Morris, E. Rolls, R. J. Dolan , 1997
"... this paper we introduce the idea of explaining responses, in one cortical area, in terms of an interaction between the influence of another area and some experimental (sensory or task-related) parameter. We refer to these effects as psychophysiological interactions and relate them to interactions b ..."
Abstract - Cited by 376 (21 self) - Add to MetaCart
this paper we introduce the idea of explaining responses, in one cortical area, in terms of an interaction between the influence of another area and some experimental (sensory or task-related) parameter. We refer to these effects as psychophysiological interactions and relate them to interactions

Model-Based Interpretation of 3D Medical Images

by A. Hill, A. Thornham, C. J. Taylor - In British Machine Vision Conference , 1993
"... The automatic segmentation and labelling of anatomical structures in 3D medical imagesis a challenging task of practical importance. We describe amodel- based approach which allows robust and accurate interpretation using explicit anatomical knowledge. Our method is based on the extension to 3D o ..."
Abstract - Cited by 45 (7 self) - Add to MetaCart
The automatic segmentation and labelling of anatomical structures in 3D medical imagesis a challenging task of practical importance. We describe amodel- based approach which allows robust and accurate interpretation using explicit anatomical knowledge. Our method is based on the extension to 3D

Online learning for matrix factorization and sparse coding

by Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro , 2010
"... Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on the large-scale matrix factorization problem that consists of learning the basis set in order to ad ..."
Abstract - Cited by 330 (31 self) - Add to MetaCart
to adapt it to specific data. Variations of this problem include dictionary learning in signal processing, non-negative matrix factorization and sparse principal component analysis. In this paper, we propose to address these tasks with a new online optimization algorithm, based on stochastic approximations

Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation

by Nikos Paragios, Rachid Deriche - INTERNATIONAL JOURNAL OF COMPUTER VISION , 2002
"... This paper presents a novel variational framework to deal with frame partition problems in Computer Vision. This framework exploits boundary and region-based segmentation modules under a curve-based optimization objective function. The task of supervised texture segmentation is considered to demonst ..."
Abstract - Cited by 312 (9 self) - Add to MetaCart
This paper presents a novel variational framework to deal with frame partition problems in Computer Vision. This framework exploits boundary and region-based segmentation modules under a curve-based optimization objective function. The task of supervised texture segmentation is considered

Automatic interpretation and coding of face images using flexible models

by Andreas Lanitis, Chris J. Taylor, Timothy F. Cootes - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1997
"... Abstract—Face images are difficult to interpret because they are highly variable. Sources of variability include individual appearance, 3D pose, facial expression, and lighting. We describe a compact parametrized model of facial appearance which takes into account all these sources of variability. T ..."
Abstract - Cited by 237 (9 self) - Add to MetaCart
Abstract—Face images are difficult to interpret because they are highly variable. Sources of variability include individual appearance, 3D pose, facial expression, and lighting. We describe a compact parametrized model of facial appearance which takes into account all these sources of variability

Feedback and self-regulated learning: A theoretical synthesis

by Deborah L. Butler, Philip H. Winne, Simon Fraser Unnversity - Review of Educational Research , 2005
"... Self-regulated learning (SRL) is a pivot upon which students ' achievement turns. We explain how feedback is inherent in and a prime determiner of processes that constitute SRL, and review areas of research that elaborate contemporary models of how feedback funciions in learning. Specifically, ..."
Abstract - Cited by 304 (7 self) - Add to MetaCart
, we begin by synthesizing a model of self-regulaiion based on contemporary educational and psychological literatures. Then we use that model as a structure for analyzing the cognitive processes involved in self-regulation, and for interpreting and integrating findings from disparate research tradi

Hierarchical Bayesian Inference in the Visual Cortex

by Tai Sing Lee, David Mumford , 2002
"... this paper, we propose a Bayesian theory of hierarchical cortical computation based both on (a) the mathematical and computational ideas of computer vision and pattern the- ory and on (b) recent neurophysiological experimental evidence. We ,2 have proposed that Grenander's pattern theory 3 coul ..."
Abstract - Cited by 300 (2 self) - Add to MetaCart
, however, was rather limited, dealing only with binary images. Moreover, its feedback mechanisms were engaged only during the learning of the feedforward connections but not during perceptual inference, though the Gibbs sampling process for inference can potentially be interpreted as top-down feedback

Learning the Semantics of Words and Pictures

by Kobus Barnard, David Forsyth , 2000
"... We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features. The model is very promising for information retrieval tasks such as database browsing and searching for images based on ..."
Abstract - Cited by 274 (12 self) - Add to MetaCart
We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features. The model is very promising for information retrieval tasks such as database browsing and searching for images based

The Design and Implementation of an Operating System to Support Distributed Multimedia Applications

by Ian Leslie, Derek Mcauley, Richard Black, Timothy Roscoe, Paul Barham, David Evers, Robin Fairbairns, Eoin Hyden , 1996
"... Support for multimedia applications by general purpose computing platforms has been the subject of considerable research. Much of this work is based on an evolutionary strategy in which small changes to existing systems are made. The approach adopted here is to start ab initio with no backward compa ..."
Abstract - Cited by 291 (22 self) - Add to MetaCart
implementation on a number of hardware platforms is described. I. Introduction G ENERAL purpose multimedia computing platforms should endow text, images, audio and video with equal status: interpreting an audio or video stream should not be a privileged task of special functions provided by the operating system
Results 11 - 20 of 6,836