14 March 2013 Hand gesture recognition based on motion history images for a simple human-computer interaction system
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Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87684M (2013); doi: 10.1117/12.2011383
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore
Abstract
A human-computer interaction can be developed using several kind of tools. One choice is using images captured using a camera. This paper proposed a simple human-computer interaction system based on hand movement captured by a web camera. The system aims to classify the captured movement into one of three classes. The first two classes contain hand movements to the left and right, respectively. The third class contains non-hand movements or hand movements to other directions. The method used in this paper is based on Motion History Images (MHIs) and nearest neighbor classifier. The resulting MHIs are processed in two manners, namely by summing the pixel values along the vertical axis and reshaping into vectors. We also use two distance criteria in this paper, respectively the Euclidian distance and cross correlation. This paper compared the performance of the combinations of different MHI data processing and distance criteria using 10 runs of 2-fold cross validation. Our experiments show that reshaping the MHI data into vectors combined with a Euclidean distance criterion gives the highest average accuracy, namely 55.67%.
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Ivanna K Timotius, Iwan Setyawan, "Hand gesture recognition based on motion history images for a simple human-computer interaction system", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87684M (14 March 2013); doi: 10.1117/12.2011383; http://dx.doi.org/10.1117/12.2011383
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KEYWORDS
Human-computer interaction

Cameras

Gesture recognition

Imaging systems

Image filtering

Optical filters

Binary data

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