



@book {2202,
	title = {Hand detection and tracking using the skeleton of the blob for medical rehabilitation applications},
	series = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci.},
	volume = {7325 LNCS},
	year = {2012},
	note = {Conference code: 91199Export Date: 21 November 2012Source: Scopusdoi: 10.1007/978-3-642-31298-4_16Language of Original Document: EnglishCorrespondence Address: Gil-Jim{\'e}nez, P.; Universidad de Alcal{\'a}, Alcal{\'a} de Henares, Madrid, Spain; email: pedro.gil@uah.esReferences: Breuer, P., Eckes, C., M{\"u}ller, S., Hand Gesture Recognition with a Novel IR Time-of-Flight Range Camera-A Pilot Study (2007) LNCS, 4418, pp. 247-260. , Gagalowicz, A., Philips, W. (eds.) MIRAGE 2007. Springer, Heidelberg;Chang, C., Lin, C., (2001) LIBSVM: A Library for Support Vector Machines, , http://www.csie.ntu.edu.tw/~cjlin/libsvm, software available at; 
Cole, J., Crowle, S., Austwick, G., Slater, D.H., Exploratory findings with virtual reality for phantom limb pain; from stump motion to agency and analgesia (2009) Disability and Rehabilitation, 31 (10), pp. 846-854; 
Elgammal, A., Muang, C., Hu, D., Skin detection - A short tutorial (2009) Encyclopedia of Biometrics; 
G{\'o}mez-Moreno, H., Maldonado-Basc{\'o}n, S., Gil-Jim{\'e}nez, P., Lafuente-Arroyo, S., (2010) Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition, 11 (4), pp. 917-930. , July; 
Gonz{\'a}lez, R., Woods, R., (1993) Digital Image Processing, , Addison-Wesley; 
Von Hardenberg, C., B{\'e}rard, F., Bare-hand human-computer interaction (2001) Proceedings of the 2001 Workshop on Perceptive User Interfaces, PUI 2001, pp. 1-8; 
Hsieh, C.C., Liou, D.H., Lee, D., A real time hand gesture recognition system using motion history image (2010) 2010 2nd International Conference on Signal Processing Systems (ICSPS), 2, pp. V2394-V2398. , July; 
Imai, A., Shimada, N., Shirai, Y., 3-d hand posture recognition by training contour variation (2004) Proceedings of Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 895-900. , May; 
Isaacs, J., Foo, J., Hand pose estimation for american sign language recognition (2004) Southern Symposium on System Theory, pp. 132-136; 
Lakshmi, J.K., Punithavalli, M., A survey on skeletons in digital image processing (2009) Digital Image Processing, pp. 260-269; 
Letessier, J., B{\'e}rard, F., Visual tracking of bare fingers for interactive surfaces (2004) Proceedings of the 17th Annual ACM Symposium on User Interface Software and Technology, UIST 2004, pp. 119-122. , ACM; 
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McCabe, C.S., Haigh, R.C., Ring, E.F., Halligan, P.W., Wall, P.D., Blake, D.R., A controlled pilot study of the utility of mirror visual feedback in the treatment of complex regional pain syndrome (type 1) (2003) Rheumatology, 42 (1), pp. 97-101; 
Murray, C.D., Patchick, E., Pettifer, S., Howard, T., Caillette, F., Kulkarni, J., Bamford, C., Investigating the efficacy of a virtual mirror box in treating phantom limb pain in a sample of chronic sufferers (2006) Disabil Human Dev., 5 (3), pp. 227-234; 
Nope, R., Sandra, E., Humberto Loaiza, C., Eduardo Caicedo, B., Estudio omparativo de t{\'e}cnicas para el reconocimiento de gestos por visi{\'o}n artificial (2009) Avances en Sistemas e Informtica, 5 (3); 
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Pugeault, N., Bowden, R., Spelling it out: Real-time ASL fingerspelling recognition IEEE Workshop on Consumer Depth Cameras for Computer Vision (2011); 
Ren, Z., Meng, J., Yuan, J., Zhang, Z., Robust hand gesture recognition with kinect sensor (2011) Proceedings of the 19th ACM International Conference on Multimedia, MM 2011, pp. 759-760. , ACM; 
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},
	month = {2012///},
	pages = {130 - 137},
	address = {Aveiro},
	abstract = {This article presents an image processing application for hand detection and tracking using the 4-connected skeleton of the segmentation mask. The system has been designed to be used with techniques of virtual reality to develop an interactive application for phantom limb pain reduction in therapeutic treatments. One of the major contributions is the design of a fast and accurate skeleton extractor, that has proven to be faster than those available in the literature. The skeleton allows the system to precisely detect the position of all the interest points of the hand (namely the fingers and the hand center). The system, composed of both the hand detector and tracker, and the virtual reality application, can work in real-time, allowing the patient to watch the virtual image of his own hand on a screen. {\textcopyright} 2012 Springer-Verlag.},
	keywords = {blob skeleton, Hand detection, hand detection and tracking, Image analysis, Image processing applications, Interactive applications, Musculoskeletal system, phantom limb pain reduction, Therapeutic treatments, Virtual images, virtual reality},
	isbn = {03029743 (ISSN); 9783642312977 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84864140682\&partnerID=40\&md5=39ee654bd93d52a92d0be5977cff42f7},
	author = {Gil-Jim{\'e}nez, P. and Losilla-L{\'o}pez, B. and Torres-Cueco, R. and Campilho, A. and L{\'o}pez-Sastre, R.}
}
