On Signature Invariants for Effective Motion Trajectory Recognition
International Journal of Robotics Research
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Motion trajectory reproduction from generalized signature description
Pattern Recognition
An Agent-Based Paradigm for Free-Hand Sketch Recognition
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Probabilistic cluster signature for modeling motion classes
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A new paradigm based on agents applied to free-hand sketch recognition
Expert Systems with Applications: An International Journal
Hand gesture tracking and recognition system for control of consumer electronics
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Australian sign language recognition using moment invariants
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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This paper describes a novel application of Fourier Descriptor techniques for the recognition of hand gesture trajectories. Appearance based coordinates of hand centroids and time steps are normalized to a fixed length by multirate techniques. Fourier techniques are applied to the data to produce frequency domain data that is scale and translation invariant. The results of inputting the complex harmonic data to a Probabilistic Neural Network for gesture classification are discussed. An understanding of underlying structure of gesture trajectories can be gained from modeling them as an infinite set of ellipses at given orientations. The rotation of the ellipses are visualized in the time domain as 'elliptic corkscrews'.