Photometric and geometric measurements based on multi-primary image projector

This paper presents photometric and geometric measurement methods based on a multi-primary image projector. The projector is primarily configured with a light source component and an image projection component. The light source, which can be programmed vis a computer, can reproduce any spectral curve. Spatial images are projected by a digital mirror device (DMD) chip that provides rapid control of the intensity of the light source spectra. The multi-primary images are reproduced by multiplexing the time-sequential 2D image pattern projections with various primary illuminant spectra. In this paper, we also apply the projector to photometric and geometric measurements. The first application, photometric measurement, is to one-shot-type camera spectral sensitivity measurement in which we reproduce rainbow projection for the measurement. The second application is to geometric calibration of projected color images in which we measure the geometrical relation between the projectors and camera based on visible and invisible image projection.

[1]  Masahiro Yamaguchi,et al.  Multiprimary color display for liquid crystal display projectors using diffraction grating , 1999 .

[2]  Katsushi Ikeuchi,et al.  Camera Spectral Sensitivity and White Balance Estimation from Sky Images , 2013, International Journal of Computer Vision.

[3]  Gordon Wetzstein,et al.  The Visual Computing of Projector‐Camera Systems , 2008, SIGGRAPH '08.

[4]  Oliver Bimber,et al.  Dynamic Adaptation of Projected Imperceptible Codes , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[5]  Fumihiko Sakaue,et al.  Multiplex Image Projection Using Multi-band Projectors , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[6]  Reinhard Klein,et al.  Practical spectral characterization of trichromatic cameras , 2011, ACM Trans. Graph..

[7]  Johnny Chung Lee,et al.  Hybrid infrared and visible light projection for location tracking , 2007, UIST.

[8]  Toshio Uchiyama,et al.  Color image reproduction based on multispectral and multiprimary imaging: experimental evaluation , 2001, IS&T/SPIE Electronic Imaging.

[9]  Paul M. Hubel,et al.  A Comparison of Methods of Sensor Spectral Sensitivity Estimation , 1994, Color Imaging Conference.

[10]  Paul A. Beardsley,et al.  A self-correcting projector , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[11]  Yasushi Yagi,et al.  A System for Capturing Textured 3D Shapes Based on One-Shot Grid Pattern with Multi-band Camera and Infrared Projector , 2011, 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission.

[12]  Zhengyou Zhang,et al.  Microsoft Kinect Sensor and Its Effect , 2012, IEEE Multim..

[13]  Takahiro Okabe,et al.  Camera spectral sensitivity estimation from a single image under unknown illumination by using fluorescence , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Gordon Wetzstein,et al.  The visual computing of projector-camera systems , 2008, SIGGRAPH '08.