By Eric P. Krotkov
This publication addresses a space of belief engineering which offers with confident methods. A version of our environment is analyzed utilizing the knowledge received from a number of viewpoints of a number of disparate sensors at a number of time instants. even supposing the function of successive version construction and energetic exploration of our environment, as is mentioned during this ebook, is of serious significance, just a couple of researchers of computer notion have up to now addressed the matter in those instructions. Krotkov's publication, that is a amendment and continuation of his hugely winning dissertation, makes a speciality of energetic exploratory sensing within the context of spatial format conception. He makes use of stereo and concentration to procure distance by way of info, and to finally advance cooperative combining suggestions. technique of a stereo procedure with verging cameras, it's proven that the space measurements might be considerably superior by way of combining assets. furthermore, the matter of merging info from the a number of perspectives is mentioned intimately. because the box of belief engineering appears of growing to be medical and utilized significance, either practitioners and researchers in desktop belief will locate this ebook a worthy addition to their libraries. RameshJain sequence Editor Acknowledgements i need to thank Professor Ruzena Bajcsy for her consistent encouragement and tips throughout the 5 years of study resulting in the dissertation upon which this publication relies. with out her assist in all concerns, this paintings might by no means were possible.
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Additional info for Active Computer Vision by Cooperative Focus and Stereo
Smaller slopes imply larger intensity variations, and the minimum slope corresponds to the point of best focus, so this criterion is to be minimized. This method performs poorly if the grey-level variations in the given direction are small compared to those in an orthogonal direction; such cases occur infrequently in natural scenes. 7 Grey-Level Variance Intuitively, high grey-level variance is associated with sharp image structure while low variance is associated with blurring, which reduces the amount of grey-level fluctuation.
10 Remarks We have presented formal criteria of "sharpness" and a number of techniques for measuring the quality of focus of an optical system, using only information in the image (no active ranging). Each, more or less directly, computes some measure of the high spatial-frequency content in the image. A criterion function computing the Fourier transform is an excellent candidate, but because of its high computational complexity and concomitant need for special-purpose hardware, it will not be considered further.
Implementation of criterion functions directly measuring the spatialfrequency distribution of the image (for example the Fourier transform) using special-purpose hardware. 4. Development of robust statistical or hardware methods for fIltering signals in non-normal noise, to minimize the temporal variations of the criterion function. S. Investigation of the performance of the range computation at object distances greater than 3 m, testing the hypothesis that the error increases quadratically with object distance.
Active Computer Vision by Cooperative Focus and Stereo by Eric P. Krotkov