@inproceedings{f7f6758ea0034c62a9155e8039ca64a4,
title = "Kinect in neurorehabilitation: Computer vision system for real time hand and object detection and distance estimation",
abstract = "This paper presents image processing and scene analysis methods that can provide artificial vision that is of interest for automatic selection of hand trajectory and prehension. The new algorithm, which uses data from the Kinect sensor, allows real-time detection of the hand of the person grasping an object at working table in front of that person. The outputs are real world coordinates of the hand and the object. The image processing is done in Matlab over the depth image stream taken from the Microsoft Kinect as a sensory input. Results show that in the presented system setup our program is capable of tracking hand movements in the transverse plane and estimating hand and object position in real-time with tolerable estimation error for the selection of stimulation paradigm that could control hand trajectory.",
keywords = "functional electrical therapy, hand tracking, Microsoft Kinect, object detection, RANSAC optimization",
author = "Matija {\v S}trbac and Marko Markovi{\'c} and Popovi{\'c}, \{Dejan B.\}",
year = "2012",
doi = "10.1109/NEUREL.2012.6419983",
language = "English",
isbn = "9781467315722",
series = "11th Symposium on Neural Network Applications in Electrical Engineering,NEUREL 2012 - Proceedings",
pages = "127--132",
booktitle = "11th Symposium on Neural Network Applications in Electrical Engineering,NEUREL 2012 - Proceedings",
note = "2012 9th International Conference on High Capacity Optical Networks and Enabling Technologies, HONET 2012 ; Conference date: 14-12-2012 Through 14-12-2012",
}