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2016 | OriginalPaper | Chapter

Rapid Vehicle Retrieval Using a Cascade of Interest Regions

Authors : Yuanqi Su, Bonan Cuan, Xingjun Zhang, Yuehu Liu

Published in: Advances in Multimedia Information Processing - PCM 2016

Publisher: Springer International Publishing

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Abstract

We propose a method to retrieve the vehicle instance in a massive dataset, that utilizes a cascaded structure to rapidly discard most irrelevant instances. The structure gradually locates the discriminative parts of a vehicle. Rather than focusing on complex and complicated features, we employ a set of prime locating and matching methods successively. During the process, texture features are utilized for localizing the windshield and license plate. Afterwards, vehicle color and type matching are conducted in the located regions of interest. To evaluate the proposed algorithm, we build a dataset comprising approximately 1000 pictures, and experiments show that our algorithm works on the dataset.

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previous chapter Creating Spectral Words for Large-Scale Hyperspectral Remote Sensing Image Retrieval
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Metadata
Title
Rapid Vehicle Retrieval Using a Cascade of Interest Regions
Authors
Yuanqi Su
Bonan Cuan
Xingjun Zhang
Yuehu Liu
Copyright Year
2016
Book
Advances in Multimedia Information Processing - PCM 2016

Print ISBN: 978-3-319-48895-0

Electronic ISBN: 978-3-319-48896-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48896-7_13