Name
Title | ||
|---|---|---|
A New Clothing Image Retrieval Algorithm Based On Sketch Component Segmentation In Mobile Visual Sensors |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1177/1550147718815627 | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS |
Keywords | Field | DocType |
Sketch-based clothing image retrieval, component segmentation, mobile visual sensors | Computer vision,Segmentation,Computer science,Image retrieval,Clothing,Artificial intelligence,Sketch,Distributed computing | Journal |
Volume | Issue | ISSN |
14 | 11 | 1550-1477 |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao-Peng Lei | 1 | 4 | 2.41 |
| Yugen Yi | 2 | 92 | 15.25 |
| Yuhua Li | 3 | 19 | 8.06 |
| Guoliang Luo | 4 | 0 | 0.68 |
| Mingwen Wang | 5 | 315 | 38.28 |