Name
Abstract | ||
|---|---|---|
A novel Bag-of-Visual-Word BoVW based approach is developed in this paper to facilitate more effective Sketch-based Image Retrieval SBIR. We focus on constructing the visual vocabulary based on the BoVW representation with both the spatial distribution and inter-relationship of descriptors. To optimize the sketch-image matching, the weighting quantization is created by integrating both the neighbor and spatial feature information to quantify features as visual words. We emphasize on an inverted indexing by converting an image to a trigram representation with visual words and their spatial information. Our experiments have obtained very positive results. |
Year | Venue | Field |
|---|---|---|
2016 | MMM | Spatial analysis,Computer vision,Weighting,Pattern recognition,Trigram,Computer science,Search engine indexing,Image retrieval,Artificial intelligence,Vocabulary,Visual Word,Sketch |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Jin | 1 | 78 | 14.92 |
| Chenjie Li | 2 | 1 | 0.69 |
| Zheming Wang | 3 | 30 | 8.12 |
| Yuejie Zhang | 4 | 127 | 25.82 |
| Tao Zhang | 5 | 202 | 40.44 |