• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 311,869
Next 10 →

A Visual Model Approach for Parsing

by Colonoscopy Videos, Yu Cao, Wallapak Tavanapong, Dalei Li, Junghwan Oh, Piet C. De Groen, Johnny Wong
"... Abstract. Colonoscopy is an important screening procedure for colorectal cancer. During this procedure, the endoscopist visually inspects the colon. Currently, there is no content-based analysis and retrieval system that automatically analyzes videos captured from colonoscopic procedures and provide ..."
Abstract - Add to MetaCart
. The first necessary step for the analysis is parsing for semantic units. In this paper, we propose a new visual model approach that employs visual features extracted directly from compressed videos together with audio analysis to discover important semantic units called scenes. Our experimental results show

Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories

by Li Fei-fei , 2004
"... Abstract — Current computational approaches to learning visual object categories require thousands of training images, are slow, cannot learn in an incremental manner and cannot incorporate prior information into the learning process. In addition, no algorithm presented in the literature has been te ..."
Abstract - Cited by 784 (16 self) - Add to MetaCart
Abstract — Current computational approaches to learning visual object categories require thousands of training images, are slow, cannot learn in an incremental manner and cannot incorporate prior information into the learning process. In addition, no algorithm presented in the literature has been

The Visual Analysis of Human Movement: A Survey

by D. M. Gavrila - Computer Vision and Image Understanding , 1999
"... The ability to recognize humans and their activities by vision is key for a machine to interact intelligently and effortlessly with a human-inhabited environment. Because of many potentially important applications, “looking at people ” is currently one of the most active application domains in compu ..."
Abstract - Cited by 743 (9 self) - Add to MetaCart
methodologies; they are grouped in 2-D approaches with or without explicit shape models and 3-D approaches. Where appropriate, systems are reviewed. We conclude with some thoughts about future directions. c ○ 1999 Academic Press 1.

Elastically deformable models

by Demetri Terzopoulos - Computer Graphics , 1987
"... The goal of visual modeling research is to develop mathematical models and associated algorithms for the analysis and synthesis of visual information. Image analysis and synthesis characterize the domains of computer vision and computer graphics, respectively. For nearly three decades, the vision an ..."
Abstract - Cited by 883 (20 self) - Add to MetaCart
, involves the analysis of images to infer object models. Visual modeling takes a unified approach to vision and graphics via modeling that exploits computational physics. In addition to geometry, physics-based modeling employs forces, torques, internal strain energies, and other physical quantities

Tree visualization with Tree-maps: A 2-d space-filling approach

by Ben Shneiderman - ACM Transactions on Graphics , 1991
"... this paper deals with a two-dimensional (2-d) space-filling approach in which each node is a rectangle whose area is proportional to some attribute such as node size. Research on relationships between 2-d images and their representation in tree structures has focussed on node and link representation ..."
Abstract - Cited by 534 (29 self) - Add to MetaCart
this paper deals with a two-dimensional (2-d) space-filling approach in which each node is a rectangle whose area is proportional to some attribute such as node size. Research on relationships between 2-d images and their representation in tree structures has focussed on node and link

A Compositional Approach to Performance Modelling

by Jane Hillston , 1996
"... Performance modelling is concerned with the capture and analysis of the dynamic behaviour of computer and communication systems. The size and complexity of many modern systems result in large, complex models. A compositional approach decomposes the system into subsystems that are smaller and more ea ..."
Abstract - Cited by 757 (102 self) - Add to MetaCart
Performance modelling is concerned with the capture and analysis of the dynamic behaviour of computer and communication systems. The size and complexity of many modern systems result in large, complex models. A compositional approach decomposes the system into subsystems that are smaller and more

Nonparametric model for background subtraction

by Ahmed Elgammal, David Harwood, Larry Davis - in ECCV ’00 , 2000
"... Abstract. Background subtraction is a method typically used to seg-ment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model can ..."
Abstract - Cited by 545 (17 self) - Add to MetaCart
Abstract. Background subtraction is a method typically used to seg-ment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model

Probabilistic Visual Learning for Object Representation

by Baback Moghaddam, Alex Pentland , 1996
"... We present an unsupervised technique for visual learning which is based on density estimation in high-dimensional spaces using an eigenspace decomposition. Two types of density estimates are derived for modeling the training data: a multivariate Gaussian (for unimodal distributions) and a Mixture-of ..."
Abstract - Cited by 699 (15 self) - Add to MetaCart
We present an unsupervised technique for visual learning which is based on density estimation in high-dimensional spaces using an eigenspace decomposition. Two types of density estimates are derived for modeling the training data: a multivariate Gaussian (for unimodal distributions) and a Mixture

Visual interpretation of hand gestures for human-computer interaction: A review

by Vladimir I. Pavlovic, Rajeev Sharma, Thomas S. Huang - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1997
"... The use of hand gestures provides an attractive alternative to cumbersome interface devices for human-computer interaction (HCI). In particular, visual interpretation of hand gestures can help in achieving the ease and naturalness desired for HCI. This has motivated a very active research area conc ..."
Abstract - Cited by 489 (17 self) - Add to MetaCart
concerned with computer vision-based analysis and interpretation of hand gestures. We survey the literature on visual interpretation of hand gestures in the context of its role in HCI. This discussion is organized on the basis of the method used for modeling, analyzing, and recognizing gestures. Important

A Model of Saliency-based Visual Attention for Rapid Scene Analysis

by Laurent Itti, Christof Koch, Ernst Niebur , 1998
"... A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing salie ..."
Abstract - Cited by 1748 (72 self) - Add to MetaCart
A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing
Next 10 →
Results 1 - 10 of 311,869
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University