Publicacions CVC
Home
|
Show All
|
Simple Search
|
Advanced Search
|
Add Record
|
Import
You must login to submit this form!
Login
Quick Search:
Field:
main fields
author
title
publication
keywords
abstract
created_date
call_number
contains:
...
Edit the following record:
Author
...
is Editor
Title
...
Type
Journal Article
Abstract
Book Chapter
Book Whole
Conference Article
Conference Volume
Journal
Magazine Article
Manual
Manuscript
Map
Miscellaneous
Newspaper Article
Patent
Report
Software
Year
...
Publication
...
Abbreviated Journal
...
Volume
...
Issue
...
Pages
...
Keywords
...
Abstract
The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains. In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm.
Address
...
Corporate Author
...
Thesis
Bachelor's thesis
Master's thesis
Ph.D. thesis
Diploma thesis
Doctoral thesis
Habilitation thesis
Publisher
...
Place of Publication
...
Editor
...
Language
...
Summary Language
...
Original Title
...
Series Editor
...
Series Title
...
Abbreviated Series Title
...
Series Volume
...
Series Issue
...
Edition
...
ISSN
...
ISBN
...
Medium
...
Area
...
Expedition
...
Conference
...
Notes
...
Approved
yes
no
Location
Call Number
...
Serial
Marked
yes
no
Copy
true
fetch
ordered
false
Selected
yes
no
User Keys
...
User Notes
...
User File
...
User Groups
...
Cite Key
...
Related
...
File
URL
...
DOI
...
Online publication. Cite with this text:
...
Location Field:
don't touch
add
remove
my name & email address
Home
SQL Search
|
Library Search
|
Show Record
|
Extract Citations
Help