Name
Title | ||
|---|---|---|
Feature alignment approach for hand posture recognition based on curvature scale space |
Abstract | ||
|---|---|---|
One of the most important aspects of gesture recognition is recognizing hand postures. Much research has been devoted to extracting reliable features for hand posture recognition. In this paper, a new feature alignment approach for hand posture recognition based on curvature scale space (CSS) is presented. The basis point for alignment is based on the two-dimensional distribution of a coordinate-peak set of the CSS image instead of on the coordinate with the maximal peak. A convolution operation is performed with the sequence of a coordinate-peak set and a predefined function. The coordinate with the maximal convolution value is designated as a basis point for aligning the CSS features of the hand posture. Results show that the proposed approach performs well in recognizing hand postures. Furthermore, the proposed approach is more accurate than previous methods based on conventional features. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.neucom.2007.12.035 | Neurocomputing |
Keywords | Field | DocType |
curvature scale space,css image,css feature,convolution operation,new feature alignment approach,hand posture,hand posture recognition,coordinate-peak set,gesture recognition,basis point,convolution operator | Computer vision,Pattern recognition,Convolution,Gesture recognition,Feature matching,Artificial intelligence,Curvature scale space,Mathematics,Posture recognition | Journal |
Volume | Issue | ISSN |
71 | 10-12 | Neurocomputing |
Citations | PageRank | References |
6 | 0.49 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chin-Chen Chang | 1 | 12 | 2.37 |
| Cheng-Yi Liu | 2 | 6 | 0.49 |
| Wen-Kai Tai | 3 | 119 | 16.71 |