Stroke Correspondence Construction Using Manifold Learning
| dc.contributor.author | Liu, Dongquan | en_US |
| dc.contributor.author | Chen, Quan | en_US |
| dc.contributor.author | Yu, Jun | en_US |
| dc.contributor.author | Gu, Huiqin | en_US |
| dc.contributor.author | Tao, Dacheng | en_US |
| dc.contributor.author | Seah, Hock Soon | en_US |
| dc.contributor.editor | Eduard Groeller and Holly Rushmeier | en_US |
| dc.date.accessioned | 2015-02-27T16:45:31Z | |
| dc.date.available | 2015-02-27T16:45:31Z | |
| dc.date.issued | 2011 | en_US |
| dc.description.abstract | Stroke correspondence construction is a precondition for generating inbetween frames from a set of key frames. In our case, each stroke in a key frame is a vector represented as a Disk B‐Spline Curve (DBSC) which is a flexible and compact vector format. However, it is not easy to construct correspondences between multiple DBSC strokes effectively because of the following points: (1) with the use of shape descriptors, the dimensionality of the feature space is high; (2) the number of strokes in different key frames is usually large and different from each other and (3) the length of corresponding strokes can be very different. The first point makes matching difficult. The other two points imply ‘many to many’ and ‘part to whole’ correspondences between strokes. To solve these problems, this paper presents a DBSC stroke correspondence construction approach, which introduces a manifold learning technique to the matching process. Moreover, in order to handle the mapping between unequal numbers of strokes with different lengths, a stroke reconstruction algorithm is developed to convert the ‘many to many’ and ‘part to whole’ stroke correspondences to ‘one to one’ compound stroke correspondence. | en_US |
| dc.description.number | 8 | |
| dc.description.seriesinformation | Computer Graphics Forum | en_US |
| dc.description.volume | 30 | |
| dc.identifier.issn | 1467-8659 | en_US |
| dc.identifier.uri | https://doi.org/10.1111/j.1467-8659.2011.01969.x | en_US |
| dc.publisher | The Eurographics Association and Blackwell Publishing Ltd. | en_US |
| dc.title | Stroke Correspondence Construction Using Manifold Learning | en_US |