@inproceedings{1327338881a44776b9bab9878da4d0f5,
title = "Hierarchical elastic graph matching for hand gesture recognition",
abstract = "This paper proposes a hierarchical scheme for elastic graph matching hand posture recognition. The hierarchy is expressed in terms of weights assigned to visual features scattered over an elastic graph. The weights in graph's nodes are adapted according to their relative ability to enhance the recognition, and determined using adaptive boosting. A dictionary representing the variability of each gesture class is proposed, in the form of a collection of graphs (a bunch graph). Positions of nodes in the bunch graph are created using three techniques: manually, semi-automatic, and automatically. The recognition results show that the hierarchical weighting on features has significant discriminative power compared to the classic method (uniform weighting). Experimental results also show that the semi-automatically annotation method provides efficient and accurate performance in terms of two performance measures; cost function and accuracy.",
keywords = "Elastic bunch graph, Feature hierarchy, Graph matching, Hand gesture recognition",
author = "Li, {Yu Ting} and Wachs, {Juan P.}",
year = "2012",
month = sep,
day = "5",
doi = "10.1007/978-3-642-33275-3_38",
language = "English",
isbn = "9783642332746",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "308--315",
booktitle = "Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings",
note = "17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012 ; Conference date: 03-09-2012 Through 06-09-2012",
}