TY - JOUR
T1 - An information theoretic criterion for evaluating the quality of 3-D reconstructions from video
JF - Image Processing, IEEE Transactions on
Y1 - 2004
A1 - Roy-Chowdhury, A.K.
A1 - Chellapa, Rama
KW - 3D reconstruction
KW - algorithms
KW - Artificial intelligence
KW - Automated;Reproducibility of Results;Sensitivity and Specificity;Signal Processing
KW - Computer Graphics
KW - Computer-Assisted;Imaging
KW - Computer-Assisted;Software Validation;Subtraction Technique;Video Recording;
KW - Image Enhancement
KW - Image Interpretation
KW - Image reconstruction
KW - Image sequences
KW - information theoretic criterion
KW - Mutual information
KW - NOISE
KW - noise distribution
KW - optical flow equations
KW - second order moments
KW - statistical analysis
KW - Three-Dimensional;Information Storage and Retrieval;Information Theory;Movement;Pattern Recognition
KW - Video sequences
KW - video signal processing
AB - Even though numerous algorithms exist for estimating the three-dimensional (3-D) structure of a scene from its video, the solutions obtained are often of unacceptable quality. To overcome some of the deficiencies, many application systems rely on processing more data than necessary, thus raising the question: how is the accuracy of the solution related to the amount of data processed by the algorithm? Can we automatically recognize situations where the quality of the data is so bad that even a large number of additional observations will not yield the desired solution? Previous efforts to answer this question have used statistical measures like second order moments. They are useful if the estimate of the structure is unbiased and the higher order statistical effects are negligible, which is often not the case. This paper introduces an alternative information-theoretic criterion for evaluating the quality of a 3-D reconstruction. The accuracy of the reconstruction is judged by considering the change in mutual information (MI) (termed as the incremental MI) between a scene and its reconstructions. An example of 3-D reconstruction from a video sequence using optical flow equations and known noise distribution is considered and it is shown how the MI can be computed from first principles. We present simulations on both synthetic and real data to demonstrate the effectiveness of the proposed criterion.
VL - 13
SN - 1057-7149
CP - 7
M3 - 10.1109/TIP.2004.827240
ER -