A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors
Nowadays, the state-of-the-art mobile visual sensors technology makes it easy to collect a great number of clothing images. Accordingly, there is an increasing demand for a new efficient method to retrieve clothing images by using mobile visual sensors. Different from traditional keyword-based and c...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-11-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718815627 |
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| _version_ | 1832553278307565568 |
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| author | Haopeng Lei Yugen Yi Yuhua Li Guoliang Luo Mingwen Wang |
| author_facet | Haopeng Lei Yugen Yi Yuhua Li Guoliang Luo Mingwen Wang |
| author_sort | Haopeng Lei |
| collection | DOAJ |
| description | Nowadays, the state-of-the-art mobile visual sensors technology makes it easy to collect a great number of clothing images. Accordingly, there is an increasing demand for a new efficient method to retrieve clothing images by using mobile visual sensors. Different from traditional keyword-based and content-based image retrieval techniques, sketch-based image retrieval provides a more intuitive and natural way for users to clarify their search need. However, this is a challenging problem due to the large discrepancy between sketches and images. To tackle this problem, we present a new sketch-based clothing image retrieval algorithm based on sketch component segmentation. The proposed strategy is to first collect a large scale of clothing sketches and images and tag with semantic component labels for training dataset, and then, we employ conditional random field model to train a classifier which is used to segment query sketch into different components. After that, several feature descriptors are fused to describe each component and capture the topological information. Finally, a dynamic component-weighting strategy is established to boost the effect of important components when measuring similarities. The approach is evaluated on a large, real-world clothing image dataset, and experimental results demonstrate the effectiveness and good performance of the proposed method. |
| format | Article |
| id | doaj-art-968a2c83e9a84650806810e7e8fb29a7 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2018-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-968a2c83e9a84650806810e7e8fb29a72025-02-03T05:54:32ZengWileyInternational Journal of Distributed Sensor Networks1550-14772018-11-011410.1177/1550147718815627A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensorsHaopeng Lei0Yugen Yi1Yuhua Li2Guoliang Luo3Mingwen Wang4School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, ChinaSchool of Software, Jiangxi Normal University, Nanchang, ChinaSoftware Engineering College, Zhengzhou University of Light Industry, Zhengzhou, ChinaEast China Jiaotong University, Nanchang, ChinaSchool of Computer and Information Engineering, Jiangxi Normal University, Nanchang, ChinaNowadays, the state-of-the-art mobile visual sensors technology makes it easy to collect a great number of clothing images. Accordingly, there is an increasing demand for a new efficient method to retrieve clothing images by using mobile visual sensors. Different from traditional keyword-based and content-based image retrieval techniques, sketch-based image retrieval provides a more intuitive and natural way for users to clarify their search need. However, this is a challenging problem due to the large discrepancy between sketches and images. To tackle this problem, we present a new sketch-based clothing image retrieval algorithm based on sketch component segmentation. The proposed strategy is to first collect a large scale of clothing sketches and images and tag with semantic component labels for training dataset, and then, we employ conditional random field model to train a classifier which is used to segment query sketch into different components. After that, several feature descriptors are fused to describe each component and capture the topological information. Finally, a dynamic component-weighting strategy is established to boost the effect of important components when measuring similarities. The approach is evaluated on a large, real-world clothing image dataset, and experimental results demonstrate the effectiveness and good performance of the proposed method.https://doi.org/10.1177/1550147718815627 |
| spellingShingle | Haopeng Lei Yugen Yi Yuhua Li Guoliang Luo Mingwen Wang A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors International Journal of Distributed Sensor Networks |
| title | A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors |
| title_full | A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors |
| title_fullStr | A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors |
| title_full_unstemmed | A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors |
| title_short | A new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors |
| title_sort | new clothing image retrieval algorithm based on sketch component segmentation in mobile visual sensors |
| url | https://doi.org/10.1177/1550147718815627 |
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