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CLC number: TP391.4

On-line Access: 2010-01-01

Received: 2009-06-26

Revision Accepted: 2009-11-28

Crosschecked: 2009-12-08

Cited: 4

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.2 P.79-91

http://doi.org/10.1631/jzus.C0910377


Computer vision based eyewear selector


Author(s):  Oscar DÉ,NIZ, Modesto CASTRILLÓ,N, Javier LORENZO, Luis ANTÓ,N, Mario HERNANDEZ, Gloria BUENO

Affiliation(s):  Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numé more

Corresponding email(s):   Oscar.Deniz@uclm.es

Key Words:  Face detection, Eye detection, Perceptual user interfaces, Human-computer interaction


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Oscar DÉNIZ, Modesto CASTRILLÓN, Javier LORENZO, Luis ANTÓN, Mario HERNANDEZ, Gloria BUENO. Computer vision based eyewear selector[J]. Journal of Zhejiang University Science C, 2010, 11(2): 79-91.

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Abstract: 
The widespread availability of portable computing power and inexpensive digital cameras are opening up new possibilities for retailers in some markets. One example is in optical shops, where a number of systems exist that facilitate eyeglasses selection. These systems are now more necessary as the market is saturated with an increasingly complex array of lenses, frames, coatings, tints, photochromic and polarizing treatments, etc. Research challenges encompass Computer Vision, Multimedia and human-computer interaction. Cost factors are also of importance for widespread product acceptance. This paper describes a low-cost system that allows the user to visualize different glasses models in live video. The user can also move the glasses to adjust its position on the face. The system, which runs at 9.5 frames/s on general-purpose hardware, has a homeostatic module that keeps image parameters controlled. This is achieved by using a camera with motorized zoom, iris, white balance, etc. This feature can be specially useful in environments with changing illumination and shadows, like in an optical shop. The system also includes a face and eye detection module and a glasses management module.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1] ABS, 2007. Smart Look. Available from http://www.smart-mirror.com [Accessed on July 30, 2007].

[2] Activisu, 2007. Activisu Expert. Available from http://www.activisu.com [Accessed on July 30, 2007].

[3] Arkin, R.C., Balch, T., 1997. AuRA: Principles and practice in review. J. Exper. Theor. Artif. Intell., 9(2-3):175-189.

[4] Azuma, R.T., 1997. A survey of augmented reality. Presence, 6:355-385.

[5] Battocchi, A., Pianesi, F., 2004. Dafex: Un Database di Espressioni Facciali Dinamiche. SLI-GSCP Workshop Comunicazione Parlata e Manifestazione delle Emozioni, p.1-11.

[6] Bouguet, J., 1999. Pyramidal Implementation of the Lucas Kanade Feature Tracker. Technical Report, OpenCV Documents, Intel Corporation, Microprocessor Research Labs.

[7] Breazeal, C., 1998. A Motivational System for Regulating Human-Robot Interaction. AAAI/IAAI, p.54-61.

[8] Cañamero, D., 1997. Modeling Motivations and Emotions as a Basis for Intelligent Behavior. Proc. 1st Int. Conf. on Autonomous Agents, p.148-155.

[9] Carl Zeiss Vision, 2007. Lens Frame Assistant. Available from http://www.zeiss.com [Accessed on July 30, 2007].

[10] Castrillón, M., Déniz, O., Hernández, M., Guerra, C., 2007. ENCARA2: real-time detection of multiple faces at different resolutions in video streams. J. Vis. Commun. Image Represent., 18(2):130-140.

[11] CBC Co., 2007. Camirror. Available from http://www.camirror.com [Accessed on July 30, 2007].

[12] CyberImaging, 2007. CyberEyes. Available from http://www.cyber-imaging.com [Accessed on July 30, 2007].

[13] Fiala, M., 2004. Artag, an Improved Marker System Based on Artoolkit. Technical Report, ERB-1111, NRC Canada.

[14] Gadanho, S.C., Hallam, J., 2001. Robot learning driven by emotions. Adapt. Behav., 9(1):42-64.

[15] GlassyEyes, 2009. Trying Eyeglasses Online. GlassyEyes Blog. Available from http://glassyeyes.blogspot.com [Accessed on Dec. 23, 2009].

[16] Jesorsky, O., Kirchberg, K.J., Frischholz, R.W., 2001. Robust face detection using the Hausdorff distance. LNCS, 2091:90-95.

[17] Just, A., Rodriguez, Y., Marcel, S., 2006. Hand Posture Classification and Recognition Using the Modified Census Transform. Proc. Int. Conf. on Automatic Face and Gesture Recognition, p.351-356.

[18] Kölsch, M., Turk, M., 2004. Robust Hand Detection. Proc. Sixth IEEE Int. Conf. on Automatic Face and Gesture Recognition, p.614-619.

[19] Kuttler, H., 2003. Seeing Is Believing. Using Virtual Try-ons to Boost Premium Lens Sales. Available from http://www.2020mag.com [Accessed on Dec. 23, 2009].

[20] Lee, J.S., Jung, Y.Y., Kim, B.S., Ko, S.J., 2001. An advanced video camera system with robust AF, AE and AWB control. IEEE Trans. Consum. Electron., 47(3):694-699.

[21] Lepetit, V., Vacchetti, L., Thalmann, D., Fua, P., 2003. Fully Automated and Stable Registration for Augmented Reality Applications. Proc. 2nd IEEE and ACM Int. Symp. on Mixed and Augmented Reality, p.93-102.

[22] Li, S., Zhu, L., Zhang, Z., Blake, A., Zhang, H., Shum, H., 2002. Statistical learning of multi-view face detection. LNCS, 2353:67-81.

[23] Low, K.H., Leow, W.K., Ang, M.H.Jr., 2002. Integrated Planning and Control of Mobile Robot with Self-Organizing Neural Network. Proc. 18th IEEE Int. Conf. on Robotics and Automation, p.3870-3875.

[24] Lyu, M.R., King, I., Wong, T.T., Yau, E., Chan, P.W., 2005. ARCADE: Augmented Reality Computing Arena for Digital Entertainment. Proc. IEEE Aerospace Conf., p.1-9.

[25] Morgan, E., 2004. Dispensing's New Wave. Eyecare Business. Available from http://www.eyecarebiz.com [Accessed on Dec. 23, 2009].

[26] Nanda, H., Cutler, R., 2001. Practical Calibrations for a Real-Time Digital Omnidirectional Camera. Proc. Computer Vision and Pattern Recognition Conf., p.3578-3596.

[27] OfficeMate Software Systems, 2007. iPointVTO. Available from http://www.opticalinnovations.com [Accessed on July 30, 2007].

[28] Picard, R., 1997. Affective Computing. MIT Press, Cambridge, MA.

[29] Practice, P., 2007. FrameCam. Available from http://www.paperlesspractice.com [Accessed on July 30, 2007].

[30] Reimondo, A., 2007. OpenCV Swiki. Available from http://www.alereimondo.no-ip.org/OpenCV/ [Accessed on Dec. 23, 2009].

[31] Roberts, K., Threlfall, I., 2006. Modern dispensing tools. Options for customised spectacle wear. Optometry Today, 46(12):26-31.

[32] Rodenstock, 2007. ImpressionIST. Available from http://www.rodenstock.com [Accessed on July 30, 2007].

[33] Sanchez-Nielsen, E., Anton-Canalis, L., Guerra-Artal, C., 2005. An autonomous and user-independent hand posture recognition system for vision-based interface tasks. LNCS, 4177:113-122.

[34] Schneiderman, H., Kanade, T., 2000. A Statistical Method for 3D Object Detection Applied to Faces and Cars. IEEE Conf. on Computer Vision and Pattern Recognition, p.1746-1759.

[35] Stenger, B., Thayananthan, A., Torr, P., Cipolla, R., 2004. Hand pose estimation using hierarchical detection. LNCS, 3058:105-116.

[36] Storring, M., Moeslund, T., Liu, Y., Granum, E., 2004. Computer Vision Based Gesture Recognition for an Augmented Reality Interface. 4th IASTED Int. Conf. on Visualization, Imaging, and Image Processing, p.766-771.

[37] Swain, M.J., Ballard, D.H., 1991. Color indexing. Int. J. Comput. Vis., 7(1):11-32.

[38] Velasquez, J., 1997. Modeling Emotions and Other Motivations in Synthetic Agents. Proc. AAAI Conf., p.10-15.

[39] Velasquez, J., 1998. Modeling Emotion-Based Decision Making. In: Canamero, D. (Ed.), Emotional and Intelligent: The Tangled Knot of Cognition. AAAI Press, Springer Netherlands, p.164-169.

[40] Viola, P., Jones, M.J., 2004. Robust real-time face detection. Int. J. Comput. Vis., 57(2):137-154.

[41] Visionix, 2007. 3DiView 3D Virtual Try-on. Available from http://www.visionix.com [Accessed on July 30, 2007].

[42] Wagner, S., Alefs, B., Picus, C., 2006. Framework for a Portable Gesture Interface. Proc. 7th Int. Conf. on Automatic Face and Gesture Recognition, p.275-280.

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