TY - JOUR
T1 - A computer vision system for on-screen item selection by finger pointing
AU - Lee, M. S.
AU - Weinshall, D.
AU - Cohen-Solal, E.
AU - Colmenarez, A.
AU - Lyons, D.
PY - 2001
Y1 - 2001
N2 - Pointing at planar surfaces such as TV and computer monitors or projection screens can be a useful mode of interaction between humans and machines. To a large extent what seems to hinder the use of vision in such practical applications is the difficulty of the computational task, which is typically defined as 3-D reconstruction from uncalibrated 2-D images of a non-static scene. We describe below two designs where, using one or two cameras, the target of pointing on a flat monitor or screen is identified without 3-D inference, using only image morphing and line intersection. This is accomplished by registering the images with the target plane. When used to identify a pointing target on a surface hiden from the camera (e.g., a computer monitor which supports the camera itself as in most PC configurations), we add aperture(s) coplanar with the target surface in front of the camera(s). We describe experimental results showing a fully automated procedure for pointing target detection with high accuracy. The simplicity of our method and its robustness, as well as the relative accuracy of our results, can make pointing a practical means of human-machine interaction.
AB - Pointing at planar surfaces such as TV and computer monitors or projection screens can be a useful mode of interaction between humans and machines. To a large extent what seems to hinder the use of vision in such practical applications is the difficulty of the computational task, which is typically defined as 3-D reconstruction from uncalibrated 2-D images of a non-static scene. We describe below two designs where, using one or two cameras, the target of pointing on a flat monitor or screen is identified without 3-D inference, using only image morphing and line intersection. This is accomplished by registering the images with the target plane. When used to identify a pointing target on a surface hiden from the camera (e.g., a computer monitor which supports the camera itself as in most PC configurations), we add aperture(s) coplanar with the target surface in front of the camera(s). We describe experimental results showing a fully automated procedure for pointing target detection with high accuracy. The simplicity of our method and its robustness, as well as the relative accuracy of our results, can make pointing a practical means of human-machine interaction.
UR - http://www.scopus.com/inward/record.url?scp=0035680240&partnerID=8YFLogxK
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AN - SCOPUS:0035680240
SN - 1063-6919
VL - 1
SP - I1026-I1033
JO - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
JF - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
T2 - 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Y2 - 8 December 2001 through 14 December 2001
ER -