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Content Provider | IEEE Xplore Digital Library |
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Author | Shuyuan Yu Shibao Zheng Hua Yang Longfei Liang |
Copyright Year | 2013 |
Description | Author affiliation: Bocom Smart Network Technol. Inc., Shanghai, China (Longfei Liang) || Dept. of EE, Shanghai Jiaotong Univ., Shanghai, China (Shuyuan Yu; Shibao Zheng; Hua Yang) |
Abstract | The recognition of vehicle manufacturer logo is a crucial and very challenging problem, which is still an area with few published effective methods. This paper proposes a new fast and reliable system for Vehicle Logo Recognition (VLR) based on Bag-of-Words (BoW). In our system, vehicle logo images are represented as histograms of visual words and classified by SVM in three steps: firstly, extract dense-SIFT features; secondly, quantize features into visual words by `Soft-assignment' thirdly, build histograms of visual words with spatial information. Compared with traditional VLR methods, experiment results show that our proposed system achieves higher recognition accuracy with less processing time. The proposed system is evaluated on a dataset of 840 low-resolution vehicle logo images with about 30×30 pixels, which verifies that our system is practical and effective. |
Starting Page | 353 |
Ending Page | 358 |
File Size | 687958 |
Page Count | 6 |
File Format | |
ISBN | 9781479907038 |
DOI | 10.1109/AVSS.2013.6636665 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-08-27 |
Publisher Place | Poland |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Support vector machines Visualization Histograms Accuracy Image recognition Feature extraction Vehicles |
Content Type | Text |
Resource Type | Article |
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