Applications of hand feature points detection and localization algorithms

Growing interest in hand gesture recognition system, bring new possibilities in developing new ways of intuitive control. Controlling the everyday surrounding can be much easier with use of natural body language. This article presents the review of hand gestures systems basing on color images, focusing on hand feature points detection. Additionally, the ways of hand feature points control possibilities are discussed, along with possible examples of hand gestures control. Hand gestures are introduced with discussion about their usage in everyday equipment control.

[1]  Michal Niezabitowski,et al.  Comparison of Hand Feature Points Detection Methods , 2014, DoCEIS.

[2]  Tadeusz Szkodny,et al.  Planning and Realization of Singular Trajectories of Adept Six 300 Robot , 2015, ICIRA.

[3]  Makoto Mizukawa,et al.  Fast Hand Feature Extraction Based on Connected Component Labeling, Distance Transform and Hough Transform , 2009, J. Robotics Mechatronics.

[4]  Nikos Papamarkos,et al.  Hand gesture recognition using a neural network shape fitting technique , 2009, Eng. Appl. Artif. Intell..

[5]  Wolfgang Hürst,et al.  Gesture-based interaction via finger tracking for mobile augmented reality , 2011, Multimedia Tools and Applications.

[6]  Artur Babiarz.  On mathematical modelling of the human arm using switched linear system , 2014 .

[7]  Artur Babiarz.  On Control of Human Arm Switched Dynamics , 2015, ICMMI.

[8]  Toyin Osunkoya,et al.  Gesture-Based Human-Computer-Interaction Using Kinect for Windows Mouse Control and PowerPoint Presentation , 2013 .

[9]  Wei-Po Lee,et al.  A smart TV system with body-gesture control, tag-based rating and context-aware recommendation , 2014, Knowl. Based Syst..

[10]  Krzysztof Jaskot,et al.  The dynamics of the human arm with an observer for the capture of body motion parameters , 2013 .

[11]  Jakub Nalepa,et al.  Spatial-based skin detection using discriminative skin-presence features , 2014, Pattern Recognit. Lett..

[12]  Jakub M. Tomczak,et al.  Advances in Intelligent Systems and Computing , 2015 .

[13]  Jakub Nalepa,et al.  Real-Time Wrist Localization in Hand Silhouettes , 2013, CORES.

[14]  Hyunseung Choo,et al.  Smart TV: are they really smart in interacting with people? Understanding the interactivity of Korean Smart TV , 2013, Behav. Inf. Technol..

[15]  Jerzy Klamka,et al.  Controllability and minimum energy control of linear fractional discrete-time infinite-dimensional systems , 2014, 11th IEEE International Conference on Control & Automation (ICCA).

[16]  Adrian Legowski,et al.  Robot Manipulator Teaching Techniques with Use of Hand Gestures , 2015, 2015 20th International Conference on Control Systems and Computer Science.

[17]  Artur Babiarz,et al.  KUKA Robot Motion Planning Using the 1742 NI Smart Camera , 2013, ICMMI.

[18]  Yi Li,et al.  Features extraction from hand images based on new detection operators , 2011, Pattern Recognit..

[19]  Yoichi Sato,et al.  Fast tracking of hands and fingertips in infrared images for augmented desk interface , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[20]  Luis M. Camarinha-Matos,et al.  Technological Innovation for Collective Awareness Systems , 2014, IFIP Advances in Information and Communication Technology.

[21]  Aitor J. Garrido,et al.  Neural control for voltage dips ride-through of oscillating water column-based wave energy converter equipped with doubly-fed induction generator , 2012 .

[22]  Jerzy Klamka,et al.  An approach to observability analysis and estimation of human arm model , 2014, 11th IEEE International Conference on Control & Automation (ICCA).