Paper Info
Title
A new framework for online sketch-based image retrieval in web environment
Abstract
We present a novel framework for retrieval of images, based on the user's sketches performed in web environment. Unlike previous approaches, our method is capable of online retrieval and provides balanced trade-off between computational cost and robustness, while still preserving local properties. In our approach novel combination of features is introduced, which describes properties of desired results and query images. Based on the extracted features we use nearest neighbor recognizer, trained on dynamic neighborhoods, in combination with k-means and k-D tree technique for further speedup. A novel technique for online retrieval, based on sequential input processing and partial hierarchical score evaluation, is introduced, allowing us to suggest on the fly entries based on in-progress sketch. We tested our method on small and large scale databases and achieved promising results. The solution itself is implemented in collaborative environment, what allows users to produce queries cooperatively.
Year
DOI
Venue
2012
10.1109/ISSPA.2012.6310525
Information Science, Signal Processing and their Applications
Keywords
Field
DocType
Internet,feature extraction,image retrieval,trees (mathematics),Web environment,collaborative environment,dynamic neighborhood,feature extraction,in-progress sketch,k-D tree technique,k-means technique,nearest neighbor recognizer,online sketch-based image retrieval,partial hierarchical score evaluation,query image,sequential input processing
Computer science,Image retrieval,Robustness (computer science),Artificial intelligence,Speedup,Sketch,The Internet,k-nearest neighbors algorithm,Computer vision,Information retrieval,Pattern recognition,Feature extraction,Visual Word
Conference
ISBN
Citations 
PageRank 
978-1-4673-0380-4
4
0.41
References 
Authors
2
3
Name
Order
Citations
PageRank
Lukas Tencer140.41
Marta Reznáková2204.02
Mohamed Cheriet32047238.58