Title :
Vehicle logo recognition based on Bag-of-Words
Author :
Shuyuan Yu ; Shibao Zheng ; Hua Yang ; Longfei Liang
Author_Institution :
Dept. of EE, Shanghai Jiaotong Univ., Shanghai, China
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.
Keywords :
image recognition; road vehicles; support vector machines; traffic engineering computing; transforms; Bag-of-Words; BoW; SIFT features; SVM; VLR; spatial information; vehicle logo images; vehicle logo recognition; vehicle manufacturer logo; visual words; Accuracy; Feature extraction; Histograms; Image recognition; Support vector machines; Vehicles; Visualization;
Conference_Titel :
Advanced Video and Signal Based Surveillance (AVSS), 2013 10th IEEE International Conference on
Conference_Location :
Krakow
DOI :
10.1109/AVSS.2013.6636665
