A Natural User Interface Translation Tool: From Sign Language to Spoken Text and Vice

[1]  S. Chiba,et al.  Dynamic programming algorithm optimization for spoken word recognition , 1978 .

[2]  Aaron E. Rosenberg,et al.  Performance tradeoffs in dynamic time warping algorithms for isolated word recognition , 1980 .

[3]  Toshio Odanaka,et al.  ADAPTIVE CONTROL PROCESSES , 1990 .

[4]  Ching Y. Suen,et al.  The State of the Art in Online Handwriting Recognition , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Benjamin Bahan,et al.  Non-manual realization of agreement in American sign language , 1996 .

[6]  David Alan Stewart,et al.  American Sign Language the easy way , 2003 .

[7]  Andy Cockburn,et al.  FingARtips: gesture based direct manipulation in Augmented Reality , 2004, GRAPHITE '04.

[8]  Meinard Müller,et al.  Information retrieval for music and motion , 2007 .

[9]  Harry Budi Santoso,et al.  Measuring the user experience , 2008 .

[10]  Hicham Noçairi,et al.  Combination of dynamic time warping and multivariate analysis for the comparison of comprehensive two-dimensional gas chromatograms: application to plant extracts. , 2009, Journal of chromatography. A.

[11]  C. Padden,et al.  Emerging Sign Languages , 2010, Languages.

[12]  Luc Van Gool,et al.  Real-time sign language letter and word recognition from depth data , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[13]  Sean Kean,et al.  Meet the Kinect: An Introduction to Programming Natural User Interfaces , 2011 .

[14]  Thad Starner,et al.  American sign language recognition with the kinect , 2011, ICMI '11.

[15]  Antonis A. Argyros,et al.  Efficient model-based 3D tracking of hand articulations using Kinect , 2011, BMVC.

[16]  Michael Riis Andersen,et al.  Kinect Depth Sensor Evaluation for Computer Vision Applications , 2012 .

[17]  Andy Beane 3D Animation Essentials , 2012 .