The Kinematic Theory Produces Human-Like Stroke Gestures
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[1] R Plamondon,et al. Studying the variability of handwriting patterns using the Kinematic Theory. , 2009, Human movement science.
[2] Lisa Anthony,et al. $N-protractor: a fast and accurate multistroke recognizer , 2012, Graphics Interface.
[3] I. Scott MacKenzie,et al. Accuracy measures for evaluating computer pointing devices , 2001, CHI.
[4] R. Plamondon,et al. A multi-level representation paradigm for handwriting stroke generation. , 2006, Human movement science.
[5] Radu-Daniel Vatavu,et al. Understanding the consistency of users' pen and finger stroke gesture articulation , 2013, Graphics Interface.
[6] Réjean Plamondon,et al. Training of On-Line Handwriting Text Recognizers with Synthetic Text Generated Using the Kinematic Theory of Rapid Human Movements , 2014, 2014 14th International Conference on Frontiers in Handwriting Recognition.
[7] Timothy D. Lee,et al. Motor Control and Learning: A Behavioral Emphasis , 1982 .
[8] Radu-Daniel Vatavu,et al. Relative accuracy measures for stroke gestures , 2013, ICMI '13.
[9] Christian O'Reilly,et al. Neuromuscular Representation and Synthetic Generation of Handwritten Whiteboard Notes , 2014, 2014 14th International Conference on Frontiers in Handwriting Recognition.
[10] Sascha E. Engelbrecht,et al. Minimum Principles in Motor Control. , 2001, Journal of mathematical psychology.
[11] Yang Li,et al. Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes , 2007, UIST.
[12] Shumin Zhai,et al. A comparative evaluation of finger and pen stroke gestures , 2012, CHI.
[13] Réjean Plamondon,et al. Personal digital bodyguards for e-security, e-learning and e-health: A prospective survey , 2018, Pattern Recognit..
[14] Réjean Plamondon,et al. The kinematic theory and minimum principles in motor control : a conceptual comparison , 2008 .
[15] Atau Tanaka,et al. Adaptive Gesture Recognition with Variation Estimation for Interactive Systems , 2014, ACM Trans. Interact. Intell. Syst..
[16] Réjean Plamondon,et al. A kinematic theory of rapid human movements , 1995, Biological Cybernetics.
[17] Wolfgang Konen,et al. Gesture recognition on few training data using Slow Feature Analysis and parametric bootstrap , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[18] Réjean Plamondon,et al. Development of a Sigma-Lognormal representation for on-line signatures , 2009, Pattern Recognit..
[19] Yang Li,et al. CrowdLearner: rapidly creating mobile recognizers using crowdsourcing , 2013, UIST.
[20] Charles E. Wright,et al. Generalized Motor Programs: Reexamining Claims of Effector Independence in Writing , 2018, Attention and Performance XIII.
[21] Réjean Plamondon,et al. A kinematic theory of rapid human movements , 1995, Biological Cybernetics.
[22] Réjean Plamondon,et al. Modelling velocity profiles of rapid movements: a comparative study , 1993, Biological Cybernetics.
[23] Thad Starner,et al. MAGIC summoning: towards automatic suggesting and testing of gestures with low probability of false positives during use , 2013, J. Mach. Learn. Res..
[24] Yann LeCun,et al. Reverse TDNN: An Architecture For Trajectory Generation , 1991, NIPS.
[25] Stephen Grossberg,et al. The Vite Model: A Neural Command Circuit for Generating Arm and Articulator Trajectories, , 1988 .
[26] Yang Li,et al. Gesture script: recognizing gestures and their structure using rendering scripts and interactively trained parts , 2014, CHI.
[27] P. J. G. Keuss,et al. Motor aspects of handwriting : approaches to movement in graphic behavior , 1984 .
[28] Laurent Miclet,et al. Synthetic On-line Handwriting Generation by Distortions and Analogy , 2007 .
[29] Julian Fiérrez,et al. Synthetic on-line signature generation. Part II: Experimental validation , 2012, Pattern Recognit..
[30] Réjean Plamondon,et al. An interactive system for the automatic generation of huge handwriting databases from a few specimens , 2008, 2008 19th International Conference on Pattern Recognition.
[31] Christian O'Reilly,et al. Recent developments in the study of rapid human movements with the kinematic theory: Applications to handwriting and signature synthesis , 2014, Pattern Recognit. Lett..
[32] James Arvo,et al. Equation entry and editing via handwriting and gesture recognition , 2001, Behav. Inf. Technol..
[33] Richard E. Ladner,et al. Usable gestures for blind people: understanding preference and performance , 2011, CHI.
[34] Christian O'Reilly,et al. The lognormal handwriter: learning, performing, and declining , 2013, Front. Psychol..
[35] Alejandro Héctor Toselli,et al. Context-Aware Gestures for Mixed-Initiative Text Editing UIs , 2015, Interact. Comput..
[36] Stefan Schaal,et al. Dynamics systems vs. optimal control--a unifying view. , 2007, Progress in brain research.
[37] R. Plamondon,et al. The limit profile of a rapid movement velocity. , 2010, Human movement science.
[38] Shumin Zhai,et al. Using strokes as command shortcuts: cognitive benefits and toolkit support , 2009, CHI.
[39] M. Landy,et al. Statistical decision theory and trade-offs in the control of motor response. , 2003, Spatial vision.
[40] T. Flash,et al. The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[41] Luis A. Leiva,et al. Gestures à Go Go , 2015, ACM Trans. Intell. Syst. Technol..
[42] Jun Nakanishi,et al. Learning Movement Primitives , 2005, ISRR.
[43] Christian O'Reilly,et al. Synthetic Handwritten Gesture Generation Using Sigma-Lognormal Model for Evolving Handwriting Classifiers , 2010 .
[44] J. Hollerbach. An oscillation theory of handwriting , 2004, Biological Cybernetics.
[45] Réjean Plamondon,et al. Improving sigma-lognormal parameter extraction , 2015, 2015 13th International Conference on Document Analysis and Recognition (ICDAR).
[46] Shumin Zhai,et al. Foundational Issues in Touch-Surface Stroke Gesture Design - An Integrative Review , 2012, Found. Trends Hum. Comput. Interact..
[47] Radu-Daniel Vatavu,et al. Gestures as point clouds: a $P recognizer for user interface prototypes , 2012, ICMI '12.