BAS: a perceptual shape descriptor based on the beam angle statistics
Pattern Recognition Letters
Phrase structure detection in dance
Proceedings of the 12th annual ACM international conference on Multimedia
Robust symbolic representation for shape recognition and retrieval
Pattern Recognition
Robust symbolic representation for shape recognition and retrieval
Pattern Recognition
A compact shape descriptor based on the beam angle statistics
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
A shape-based model for visual information retrieval
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Variational shape matching for shape classification and retrieval
Pattern Recognition Letters
MIFT: A framework for feature descriptors to be mirror reflection invariant
Image and Vision Computing
| Hi-index | 35.68 |
This paper applies directed acyclic graphs (DAGs) to a large class of (temporal) pattern recognition problems and other recognition problems where the data has a linear ordering. The data streams are coded (DAG-coded) into DAGs for robust segmentation. The similarity of two streams can be manifested as the path matching score of the two corresponding DAGs. This paper also presents an efficient and robust dynamic programming algorithm for their comparisons (DAG-compare). Since the DAG-coding methodology directly provides a robust segmentation process, it can be applied recursively to create a novel system architecture. The DAG structure also allows adaptive restructuring, leading to a novel approach to neural information processing. By using these elementary operations on DAGs, we can recognize on average 94.0% (writer-dependent) of the isolated handwritten cursive characters. DAG-coding may also be applied to speech recognition or any other continuous streams where a robust multipath segmentation aids the recognition process