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Calibrated Imaging Lab (CIL) This lab is no longer active. Head: Simon Baker Contact: Daniel D. Morris Mailing address: Carnegie Mellon University Robotics Institute 5000 Forbes Avenue Pittsburgh, PA 15213 Associated center: VASC For more information, see this lab's homepage.

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Lab Description

A resource used by the CMU research community to obtain high quality images in a tightly controlled and yet flexible environment. A wide choice of lighting and video cameras including a cooled, very-low-noise photometrics camera are available. A six degree of freedom jig permits the cameras to be accurately positioned under computer control, and a rail and turntable permit control of an object's position.

The lab has been used to study color, texture and illumination and the impact of these on computer vision tasks such as estimating surface orientation, object segmentation and physical model creation. It has also been used to calibrate cameras (an implementation of Tsai's calibration technique is available), and to take images of objects for stereo and 3D shape reconstruction.

Past members

	Name	Title	Email Address
	Simon Baker	Adjunct Faculty (Adjunct)
	Frank Dellaert	PhD Student, CS
	Joyoni Dey	PhD Student, ECE
	John Krumm	PhD Student, RI
	Mark Maimone	Postdoctoral Fellow
	Bruce Maxwell	PhD Student, RI
	Daniel D. Morris	PhD Student, RI
	Steven Seitz	Adjunct Faculty (Adjunct)
	Steven Shafer	Associate Professor of Computer Science and Robotics (Adjunct)
	Michael Smith	PhD Student, ECE	msmith@ri.cmu.edu
	Anthony (Tony) Stentz	Research Professor/Assoc Dir NREC	tony+@cmu.edu
	Reg Willson	PhD Student, RI/ECE
	Yalin Xiong	PhD Student, RI

Past projects

Depth From Focus and Defocus - Focus interpretation is a valuable alternative to stereo vision because it doesn't require solving correspondence for depth recovery.	Image-based Modeling and Rendering - Acquiring, manipulating, and rendering representations of real environments based on photographs.
Spatial Frequency - Our space / frequency representation has proven useful for solving the combined problem of segmentation and shape from texture.	Zoom Lens Calibration - We have developed new algorithms and techniques to build models for cameras with automated zoom lenses

Recent publications [View all 34 publications]

• Moment and Hypergeometric Filters for High Precision Computation of Focus, Stereo and Optical Flow
  Y. Xiong and S. Shafer
  International Journal of Computer Vision, Vol. 22, No. 1, February, 1997, pp. 25-59.

• Segmentation and Interpolation Using Multiple Physical Hypotheses of Image Formation
  B. Maxwell
  doctoral dissertation, tech. report CMU-RI-TR-96-28, Robotics Institute, Carnegie Mellon University, July, 1996.
  Download: pdf [2251 KB], ps.gz [2620 KB] copyrighted

• Physics-Based Segmentation: Moving Beyond Color
  B. Maxwell and S. Shafer
  Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, June, 1996, pp. 742 - 749. [Abstract]
  Download: pdf [94 KB], ps.gz [103 KB] copyrighted

• Physics-Based Segmentation: Looking Beyond Color
  B. Maxwell and S. Shafer
  Proceedings of Image Understanding Workshop, 1996.
  Download: pdf [232 KB], ps.gz [274 KB] copyrighted

• Physics-Based Segmentation: Looking Beyond Color
  B. Maxwell and S. Shafer
  tech. report CMU-RI-TR-95-37, Robotics Institute, Carnegie Mellon University, October, 1995. [Abstract]
  Download: pdf [2159 KB] copyrighted

• Texture Segmentation and Shape in the Same Image
  J. Krumm and S. Shafer
  The Fifth International Conference on Computer Vision, June, 1995, pp. 121-127. [Abstract]
  Download: pdf [566 KB] copyrighted

• Dense Structure from a Dense Optical Flow Sequence
  Y. Xiong and S. Shafer
  tech. report CMU-RI-TR-95-10, Robotics Institute, Carnegie Mellon University, April, 1995. [Abstract]
  Download: pdf [903 KB], ps.gz [3049 KB], ps.z [3367 KB] copyrighted

• What is the Center of the Image?
  R. Willson and S. Shafer
  Journal of the Optical Society of America A, Vol. 11, No. 11, November, 1994, pp. 2946 - 2955. [Abstract]
  Download: pdf [1435 KB] copyrighted

• A characterizable shape-from-texture algorithm using the spectrogram
  J. Krumm and S. Shafer
  Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis, October, 1994, pp. 322 - 325. [Abstract]
  Download: pdf [372 KB] copyrighted

• Modeling and Calibration of Automated Zoom Lenses
  R. Willson
  Proceedings of the SPIE #2350: Videometrics III, October, 1994, pp. 170 - 186. [Abstract]
  Download: pdf [177 KB], ps.gz [116 KB], ps.z [241 KB] copyrighted