CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
research
Scene categorization with multi-scale category-specific visual words
Authors
J Qin
NHC Yung
Publication date
1 January 2009
Publisher
'SPIE-Intl Soc Optical Eng'
Doi
Cite
Abstract
IS&T/SPIE Conference on Intelligent Robots and Computer Vision XXVI: Algorithms and TechniquesIn this paper, we propose a scene categorization method based on multi-scale category-specific visual words. The proposed method quantizes visual words in a multi-scale manner which combines the global-feature-based and local-feature-based scene categorization approaches into a uniform framework. Unlike traditional visual word creation methods which quantize visual words from the whole training images without considering their categories, we form visual words from the training images grouped in different categories then collate the visual words from different categories to form the final codebook. This category-specific strategy provides us with more discriminative visual words for scene categorization. Based on the codebook, we compile a feature vector that encodes the presence of different visual words to represent a given image. A SVM classifier with linear kernel is then employed to select the features and classify the images. The proposed method is evaluated over two scene classification datasets of 6,447 images altogether using 10-fold cross-validation. The results show that the classification accuracy has been improved significantly comparing with the methods using the traditional visual words. And the proposed method is comparable to the best results published in the previous literatures in terms of classification accuracy rate and has the advantage in terms of simplicity. © 2009 SPIE-IS&T.published_or_final_versio
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
HKU Scholars Hub
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:hub.hku.hk:10722/155515
Last time updated on 01/06/2016
HKU Scholars Hub
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:hub.hku.hk:10722/62064
Last time updated on 01/06/2016