A dynamic protocol stack configuration model for adaptation to communications environments

SUMMARYWe first describe in a unified way how to compute the covariance matrix from the gray levels of the image. We then experimentally investigate whether or not the computed covariance matrix actually reflects the accuracy of the feature position by doing subpixel correction using variable template matching. We also test if the accuracy of the homography and the fundamental matrix can really be improved by optimization using the covariance matrix computed from the gray levels.

show abstract

Do we really have to consider covariance matrices for image feature points?

Kanazawa

Kanatani

2002

Electron Comm Jpn Pt III

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A dynamic protocol stack configuration model for adaptation to communications environments

Cited by 1 publication

References 14 publications

Do we really have to consider covariance matrices for image feature points?

Do we really have to consider covariance matrices for image feature points?

Contact Info

Product

Resources

About