@inproceedings{c5b54228bcdb4de1a41fcba175e0afef,
title = "Distance-based multiple paths quantization of vocabulary tree for object and scene retrieval",
abstract = "The state of the art in image retrieval on large scale databases is achieved by the work inspired by the text retrieval approaches. A key step of these methods is the quantization stage which maps the high-dimensional feature vectors to discriminatory visual words. This paper mainly proposes a distance-based multiple paths quantization (DMPQ) algorithm to reduce the quantization loss of the vocabulary tree based methods. In addition, a more efficient way to build a vocabulary tree is presented by using sub-vectors of features. The algorithm is evaluated on both the standard object recognition and the location recognition databases. The experimental results have demonstrated that the proposed algorithm can effectively improve image retrieval performance of the vocabulary tree based methods on both the databases.",
author = "Heng Yang and Qing Wang and Do, {Ellen Yi Luen}",
year = "2010",
doi = "10.1007/978-3-642-12307-8_29",
language = "英语",
isbn = "3642123066",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "313--322",
booktitle = "Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers",
edition = "PART 1",
note = "9th Asian Conference on Computer Vision, ACCV 2009 ; Conference date: 23-09-2009 Through 27-09-2009",
}