Convexity local contour sequences for gesture recognition
Annual ACM Symposium on Applied Computing - SAC,
pages 34--40,
- Mar 2013
Associated documents :
Algorithms for hand feature extraction used in gesture recognition systems have some problems such as unnecessary information gathering. This paper proposes a novel method for feature extraction in gesture recognition systems based on the Local Contour Sequence (LCS). It is called the Convexity Local Contour Sequence (CLCS) and represents the hand shape only with the most significant information. This generates a smaller output result, but capable to model an entire dynamic gesture. It is used to classify dynamic gestures with an Elman Recurrent Network and Hidden Markov Model and presents a better result compared to regular LCS.
@InProceedings{BJBFBF13,
author = {Barros, Pablo and Junior, Nestor and Bisneto, Juvenal and Fernandes, Bruno and Bezerra, Byron and Fernandes, Sérgio},
title = {Convexity local contour sequences for gesture recognition},
booktitle = {Annual ACM Symposium on Applied Computing - SAC},
editors = {},
number = {},
volume = {},
pages = {34--40},
year = {2013},
month = {Mar},
publisher = {Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC '13},
doi = {},
}