'Boundary detection' presentation slideshows

Boundary detection - PowerPoint PPT Presentation

A highly accurate and computationally efficient approach for unconstrained iris segmentation

A highly accurate and computationally efficient approach for unconstrained iris segmentation

A highly accurate and computationally efficient approach for unconstrained iris segmentation. Yu Chen, Malek Adjouadi *, Changan Han, Jin Wang, Armando Barreto, Naphtali Rishe, Jean Andrian,College of Engineering and Computing, Florida International University, Miami, FL 33174, USA

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539 views • 41 slides
The Cricket Location-Support System

The Cricket Location-Support System

The Cricket Location-Support System. Nissanka B. Priyantha Anit Chakraborty Hari Balakrishnan MIT Lab for Computer Science http://nms.lcs.mit.edu/. Motivation . Emergence of pervasive computing environments Context-aware applications Location-dependent behavior

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474 views • 34 slides
Hierarchical Region-Based Segmentation by Ratio-Contour

Hierarchical Region-Based Segmentation by Ratio-Contour

Course Project of CSCE 790. Hierarchical Region-Based Segmentation by Ratio-Contour. Jun Wang April 28, 2004. Background: Introduction of Image Segmentation. a) What is image segmentation?

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550 views • 33 slides
Edge Linking & Boundary Detection

Edge Linking & Boundary Detection

Edge Linking & Boundary Detection. Ideal case : Techniques detecting intensity discontinuities should yield pixels lying only on edges ( or the boundary between regions). Real life :

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3.76k views • 28 slides
Efficient Color Boundary Detection with Color-opponent Mechanisms

Efficient Color Boundary Detection with Color-opponent Mechanisms

Efficient Color Boundary Detection with Color-opponent Mechanisms. CVPR2013 Posters. Outline. Introduction Approach Experiments Conclusions. Introduction. Introduction.

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504 views • 26 slides
Dynamic Occlusion Analysis in Optical Flow Fields

Dynamic Occlusion Analysis in Optical Flow Fields

CSE 668, Animate Vision Principles for 3D Image Sequences CSE Department, SUNY Buffalo luyuzhao@buffalo.edu. Dynamic Occlusion Analysis in Optical Flow Fields. http://www.wps.cn/index.php?mod=template&app=wpp&id=256&type=browser&O=g&page=2. Optical Flow field:.

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411 views • 25 slides
Douglas Turnbull Computer Audition Lab UC San Diego, USA Gert Lanckriet , UC San Diego, USA

Douglas Turnbull Computer Audition Lab UC San Diego, USA Gert Lanckriet , UC San Diego, USA

A Supervised Approach for Detecting Boundaries in Music using Difference Features and Boosting. Douglas Turnbull Computer Audition Lab UC San Diego, USA Gert Lanckriet , UC San Diego, USA Elias Pampalk , AIST Japan Masataka Goto , AIST, Japan ISMIR September 24, 2007.

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365 views • 22 slides
Learning Scale-Invariant Contour Completion

Learning Scale-Invariant Contour Completion

Learning Scale-Invariant Contour Completion. Xiaofeng Ren, Charless Fowlkes and Jitendra Malik. Abstract.

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358 views • 22 slides
Min-Hsuan Lai Department of Computer Science & Information Engineering

Min-Hsuan Lai Department of Computer Science & Information Engineering

Automatic Prosodic Event Detection Using Acoustic, Lexical, and Syntactic Evidence Sankaranarayanan Ananthakrishnan , Shrikanth S. Narayanan IEEE 2007. Min-Hsuan Lai Department of Computer Science & Information Engineering National Taiwan Normal University. Outline. Introduction

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316 views • 17 slides
Outline

Outline

Outline. ADBOT Progress Report. Achievements Project Outputs Issues Risk Analysis Target for the next three months Project Manager: Aljon Rey P. Aniban Members: Emmanuel B. Cagadas Anna Mae C. Yap. Works that have been achieved over the past month. I. Achievements.

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392 views • 16 slides
Kyoungryol Kim

Kyoungryol Kim

Extracting Schedule Information from Korean Email. Kyoungryol Kim. Table of Contents. Introduction Methods and Experiments Discussion Schedule. Introduction. Goal. To extract schedule information, Meeting location and Speaker, automatically from Email. ????? ,

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225 views • 14 slides
UAH GRIDS Center Middleware Testing

UAH GRIDS Center Middleware Testing

UAH GRIDS Center Middleware Testing. Sandra Redman Information Technology and Systems Center and Information Technology Research Center National Space Science and Technology Center 256-961-7806 sredman@itsc.uah.edu Sandra.Redman@msfc.nasa.gov www.itsc.uah.edu.

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244 views • 12 slides
Shot boundary detection based on frame histograms analysis

Shot boundary detection based on frame histograms analysis

Shot boundary detection based on frame histograms analysis. Tomsk Polytechnic University. Vakulenko M.D. 1 , Kovalenko D.A . 2 , Tolkunov S.V. 2 , Master Students Gr. 1 -8BM10, 2 -8VM13. Scientific advisor: Dr. Sergey V. Axyonov. Motivation

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314 views • 9 slides
A Comparison of Manual and Automatic Melody Segmentation

A Comparison of Manual and Automatic Melody Segmentation

A Comparison of Manual and Automatic Melody Segmentation. Massimo Melucci Nicola Orio. Introduction. Content-based music retrieval. Random Segmentation, N-grams-based segmentation. Detect boundaries to highlight musical phrases that describe music content. Experiment.

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181 views • 8 slides

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