TY - GEN
T1 - Democratizing 3D dynamic gestures recognition
AU - Caon, Maurizio
AU - Yue, Yong
AU - Tscherrig, Julien
AU - Khaled, Omar Abou
AU - Mugellini, Elena
PY - 2013
Y1 - 2013
N2 - Developing vision-based 3D gestures recognition systems requires strong expertise and knowledge in computer vision and machine learning techniques. As human-computer interaction researchers do not generally have a thorough knowledge of these techniques, we developed Gesta. Gesta is a tool that enables non-experts in vision computing and artificial intelligence techniques to rapidly develop a 3D gestures recognition system prototype and to support the gesture design process. This tool works with up to two Microsoft Kinects, and integrates the depth cameras calibration algorithm and the hidden Markov models classifier. The users can manage these complex functions through a simple graphical user interface, even if they do not have any expertise in computer vision and machine learning domains. A usability test with 12 researchers with experience in human-computer interaction has been conducted in order to evaluate the overall usability of this tool. Results demonstrate that the testers appreciated the Gesta tool which scored 88.9 points out of 100 in the Brooke's system usability scale.
AB - Developing vision-based 3D gestures recognition systems requires strong expertise and knowledge in computer vision and machine learning techniques. As human-computer interaction researchers do not generally have a thorough knowledge of these techniques, we developed Gesta. Gesta is a tool that enables non-experts in vision computing and artificial intelligence techniques to rapidly develop a 3D gestures recognition system prototype and to support the gesture design process. This tool works with up to two Microsoft Kinects, and integrates the depth cameras calibration algorithm and the hidden Markov models classifier. The users can manage these complex functions through a simple graphical user interface, even if they do not have any expertise in computer vision and machine learning domains. A usability test with 12 researchers with experience in human-computer interaction has been conducted in order to evaluate the overall usability of this tool. Results demonstrate that the testers appreciated the Gesta tool which scored 88.9 points out of 100 in the Brooke's system usability scale.
UR - http://www.scopus.com/inward/record.url?scp=84881649519&partnerID=8YFLogxK
U2 - 10.1109/UCCV.2013.6530800
DO - 10.1109/UCCV.2013.6530800
M3 - Conference Proceeding
AN - SCOPUS:84881649519
SN - 9781467356756
T3 - 2013 1st IEEE Workshop on User-Centered Computer Vision, UCCV 2013
SP - 7
EP - 12
BT - 2013 1st IEEE Workshop on User-Centered Computer Vision, UCCV 2013
T2 - 2013 1st IEEE Workshop on User-Centered Computer Vision, UCCV 2013
Y2 - 15 January 2013 through 17 January 2013
ER -