Name
Abstract | ||
|---|---|---|
Image annotation is a fundamental and challenging task in the field of semantic image retrieval. In this paper, we deal with image annotation via matrix completion. Concretely, we formulate the problem of annotating the tags of an image into a constrained optimization problem, in which the constraint is to keep the consistency with the given initial labels and the objective is to minimize the discrepancy between the correlation in visual content and the correlation in semantic tags. We solve the optimization problem with the linearized alternating direction method. Experimental results on benchmark data demonstrate the effectiveness of our proposals. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/VCIP.2015.7457871 | 2015 Visual Communications and Image Processing (VCIP) |
Keywords | Field | DocType |
Image annotation,matrix completion,Tag Matrix Completion,linearized alternating direction method,tag based image retrieval | Computer vision,Automatic image annotation,Information retrieval,Matrix completion,Computer science,Visualization,Matrix decomposition,Image retrieval,Semantic HTML,Artificial intelligence,Optimization problem,Visual Word | Conference |
Citations | PageRank | References |
2 | 0.36 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhen Qin | 1 | 6 | 1.15 |
| Chun-Guang Li | 2 | 310 | 17.35 |
| Honggang Zhang | 3 | 440 | 33.22 |
| Jun Guo | 4 | 1579 | 137.24 |