Name
Abstract | ||
|---|---|---|
The growing popularity of tablet PCs and intelligent pen-centric computing has increased the importance of freehand sketch recognition algorithms. In this paper, the proposed method integrates the temporal, spatial and geometric constraint information to improve the recognition accuracy. To interpret the sketch as an incremental process, the paper investigates the use of the information fusion technique with Support Vector Machines (SVMs) chain for modeling and understanding the spatial and temporal information of sketch sequences. Online sketch recognition is achieved through the use of the SVMs-chain for systematically modeling the dynamic and stochastic behaviors of the sketch. To validate its efficiency, the experimental results in various domains and the comparison with traditional Hidden Markov Models have been presented. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.engappai.2011.10.001 | Eng. Appl. of AI |
Keywords | Field | DocType |
freehand sketch recognition algorithm,support vector machines,temporal information,information fusion technique,recognition accuracy,svms-chain modeling,online sketch recognition,geometric constraint information,sketch sequence,incremental process,hidden markov models,sketch recognition | Scale space filtering,Computer science,Popularity,Support vector machine,Sketch recognition,Artificial intelligence,Hidden Markov model,Information fusion,Machine learning,Sketch | Journal |
Volume | Issue | ISSN |
25 | 2 | 0952-1976 |
Citations | PageRank | References |
3 | 0.37 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kun Yang | 1 | 47 | 12.60 |
| Zhijun Li | 2 | 1051 | 56.61 |
| Jingwei Ye | 3 | 7 | 1.53 |