URL:

files/proceedings/2007/61.pdf

Abstract:

This paper describes features and the feature extraction processing which were applied for recognising gestures by artificial neural networks. The features were applied for two cases: time series of luminance rate images for hand gestures and time series of pure grey-scale images of the facial mouth region. A focus will be on the presentation and discussion of the application of 2- dimensional Fourier transformed images both for luminance rate feature maps of hand gestures and for greyscale images of the facial mouth region. Appearancebased features in this context are understood as features based on whole images, which perform well for highly articulated objects. The described approach was used based on our assumption that highly articulated objects are of great interest for musical applications.