'Similar images' diaporamas de présentation

Image Stitching

1.2k views • 63 slides

Advanced Internet Searching: Some Google, some not

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The Continuing M e t a m o r p h o s i s Of the Web

The Continuing M e t a m o r p h o s i s Of the Web. Dr. Alfred Z. Spector VP, Research and Special Initiatives Google, Inc. WWW 2009, Madrid, 24 April 2009. Outline. Federation, Reach, and Evolution Extraordinary Achievements of Note The Evolutionary Path Forward

638 views • 52 slides

Efficient Image Search and Retrieval using Compact Binary Codes

Efficient Image Search and Retrieval using Compact Binary Codes. Rob Fergus (NYU) Jon Barron (NYU/UC Berkeley) Antonio Torralba (MIT) Yair Weiss (Hebrew U.). CVPR 2008. Large scale image search. Internet contains many billions of images. How can we search them, based on visual content?.

639 views • 49 slides

Efficient Image Search and Retrieval using Compact Binary Codes

Efficient Image Search and Retrieval using Compact Binary Codes. Rob Fergus (NYU) Antonio Torralba (MIT) Yair Weiss (Hebrew U.). Large scale image search. Internet contains many billions of images. How can we search them, based on visual content?. The Challenge:

541 views • 38 slides

CONTENT BASED FACE RECOGNITION

CONTENT BASED FACE RECOGNITION. Under the guidance of Prof. Pushpak Bhattacharya . Ankur Jain 01D05007 Pranshu Sharma 01005026 Prashant Baronia 01D05005 Swapnil Zarekar 01D05001. Introduction. Problem Statement :

462 views • 27 slides

Building text features for object image classification

Building text features for object image classification. Group 1 : Eddie Sun, Youngbum Kim, Yulong Wang. Which object is presented ?. Why we need text features?. Main idea & Insights. Main idea

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Mining TV Broadcasts 24/7 for Recurring Video Sequences

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Windows Basics: Files and Folders

318 views • 17 slides

An efficient Video Coding using Phase-matched Error from Phase Correlation Information

An efficient Video Coding using Phase-matched Error from Phase Correlation Information. Manoranjan Paul 1 and Golam Sorwar 2 2008 IEEE. Outline. Introduction Propose technique Phase correlation Binary Matrix Generation using Phase Correlation Mode Selection from the Binary Matrix

380 views • 16 slides

Windows Basics: Files and Folders

353 views • 16 slides

Conic Sections

Conic Sections. An Introduction. Conic Sections - Introduction. Similar images are located on page 604 of your book. You do not need to try and recreate each drawing in your notes. Conic Sections - Introduction.

423 views • 9 slides

DISCOVIR

DISCOVIR. Contemporary ways of searching. By example. Similar images?. By sketch. Traditional. server. clients. Internet. Peer to Peer model. Internet. ?. The real one. ?. Web Site. http://www.cse.cuhk.edu.hk/~miplab/discovir.

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Senior Project Sprint #1

Senior Project Sprint #1 John McCoey Elliot Whaley Joe Charpentier Team name: TBD Product name: Picture Prowler Features Face Finder The user selects a person in a photo. The application will return a folder containing all pictures of this person from a user selected folder.

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Pair Distribution Function-Computed Tomography Scans

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Digi Pack/magazine advert

When you look at characters in photo-shoots, they usually tend to wear branded products, this creates a synergy, which allows the audience to purchase the products, which increases the profits for the brand.

70 views • 1 slides

Evdoxios Baratis, Euripides G.M. Petrakis

WebSummarization. Automatic Logo and Trademark Extraction from Web Sites. Evdoxios Baratis, Euripides G.M. Petrakis Dept. of Electr. & Comp. Engin., Technical Univ. of Crete (TUC), Greece Evangelos E. Milios Faculty of Comp. Science, Dalhousie University, Hallifax, Canada.

122 views • 1 slides

Mining Social Images with Distance Metric Learning for Automated Image Tagging

80 views • 1 slides