Name
Abstract | ||
|---|---|---|
This paper proposes a new dynamic time warping (DTW) method, called non-Markovian DTW. In the conventional DTW, the warping function is optimized generally by dynamic programming (DP) subject to some Markovian constraints which restrict the relationship between neighboring time points. In contrast, the non-Markovian DTW can introduce non-Markovian constraints for dealing with the relationship between points with a large time interval. This new and promising ability of DTW is realized by using graph cut as the optimizer of the warping function instead of DP. Specifically, the conventional DTW problem is first converted as an equivalent minimum cut problem on a graph and then edges representing the non-Markovian constraints are added to the graph. An experiment on online character recognition showed the advantage of using non-Markovian constraints during DTW. |
Year | Venue | Keywords |
|---|---|---|
2012 | Pattern Recognition | character recognition,dynamic programming,graph theory,DTW method,DTW problem,dynamic programming,edge representation,graph cut,minimum cut problem,nonMarkovian constraints,nonMarkovian dynamic time warping,online character recognition,warping function |
Field | DocType | ISSN |
Graph theory,Cut,Dynamic programming,Image warping,Markov process,Dynamic time warping,Character recognition,Pattern recognition,Computer science,Minimum cut,Artificial intelligence | Conference | 1051-4651 |
ISBN | Citations | PageRank |
978-1-4673-2216-4 | 2 | 0.38 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seiichi Uchida | 1 | 790 | 105.59 |
| Masahiro Fukutomi | 2 | 2 | 0.38 |
| Koichi Ogawara | 3 | 6 | 1.13 |
| Yaokai Feng | 4 | 2 | 0.38 |