Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Error Analysis in Stereo Determination of 3-D Point Positions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Quantization Error in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Analysis of Stereo Quantization Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Computer Vision by Cooperative Focus and Stereo
Active Computer Vision by Cooperative Focus and Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards Real-Time Cue Integration by Using Partial Results
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
3-D Depth Reconstruction from a Single Still Image
International Journal of Computer Vision
Depth estimation using monocular and stereo cues
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Continuous stereo self-calibration by camera parameter tracking
IEEE Transactions on Image Processing
Improvised Filter Design for Depth Estimation from Single Monocular Images
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
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This paper compares the performances of the binocular cues of stereo and vergence, and the monocular cue of focus for range estimation using an active vision system. The performance of each cue is characterized in terms of sensitivity to errors in the imaging parameters. The effects of random, quantization errors are expressed in terms of the standard deviation of the resulting depth error. The effect of systematic, calibration errors on estimation using each cue is also studied. Performance characterization of each cue is utilized to evaluate the relative performance of the cues. Also discussed, based on such characterization, are ways to select a cue taking into account the computational and reliability aspects of the corresponding estimation process.