Fundamentals of speech recognition
Fundamentals of speech recognition
Using Gait as a Biometric, via Phase-weighted Magnitude Spectra
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Extended Model-Based Automatic Gait Recognition of Walking and Running
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Automatic extraction and description of human gait models for recognition purposes
Computer Vision and Image Understanding
Feasibility analysis of human motion identification using motion capture
MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
Automatic gait recognition via Fourier descriptors of deformable objects
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Movement identification analysis based on motion capture
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
3D human motion tracking based on a progressive particle filter
Pattern Recognition
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The domain of biometric motion identification undergoes an extensive research and development. An adaptation of one of the motion identification solutions can be the base for an implementation of a complex identification system. Such a system will always require well defined human skeleton, motion model, comparison algorithms as well as a properly constructed motion database. The results obtained while studying the system, greatly depend on the analysis methods. The main advantage of Motion Capture (MC) systems is the accuracy of recorded data. A Captured motion contains a lot of subtle details as their source is the life person (a human actor).