@inproceedings{00ee9f264f7343cdacdc31eb5df0ba10,
title = "Relevance feedback for sketch retrieval based on linear programming classification",
abstract = "Relevance feedback plays as an important role in sketch retrieval as it does in existing content-based retrieval. This paper presents a method of relevance feedback for sketch retrieval by means of Linear Programming (LP) classification. A LP classifier is designed to do online training and feature selection simultaneously. Combined with feature selection, it can select a set of user-sensitive features and perform classification well facing a small number of training samples. Experiments prove the proposed method both effective and efficient for relevance feedback in sketch retrieval.",
keywords = "Linear Programming (LP), Relevance feedback, Sketch retrieval",
author = "Li Bin and Sun Zhengxing and Liang Shuang and Zhang Yaoye and Yuan Bo",
year = "2006",
language = "English (US)",
isbn = "3540487662",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "201--210",
booktitle = "Advances in Multimedia Information Processing - PCM 2006",
address = "Germany",
note = "PCM 2006: 7th Pacific Rim Conference on Multimedia ; Conference date: 02-11-2006 Through 04-11-2006",
}