How to Install and Uninstall klt.x86_64 Package on Fedora 34

Last updated: July 03,2024

1. Install "klt.x86_64" package

In this section, we are going to explain the necessary steps to install klt.x86_64 on Fedora 34


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                klt.x86_64
            
                    
    
    Copied

2. Uninstall "klt.x86_64" package

This guide let you learn how to uninstall klt.x86_64 on Fedora 34:


    
        
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                sudo dnf remove
            
                        
                klt.x86_64
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the klt.x86_64 package on Fedora 34

Last metadata expiration check: 2:38:53 ago on Tue Sep 6 02:10:55 2022.
Available Packages
Name : klt
Version : 1.3.4
Release : 23.fc34
Architecture : x86_64
Size : 40 k
Source : klt-1.3.4-23.fc34.src.rpm
Repository : fedora
Summary : An implementation of the Kanade-Lucas-Tomasi feature tracker
URL : http://www.ces.clemson.edu/~stb/klt/index.html
License : Public Domain
Description :
: KLT is an implementation, in the C programming language, of a
: feature tracker for the computer vision community. The source
: code is in the public domain, available for both commercial and
: non-commercial use.
:
: The tracker is based on the early work of Lucas and Kanade,
: was developed fully by Tomasi and Kanade, and was explained clearly
: in the paper by Shi and Tomasi. Later, Tomasi proposed a slight
: modification which makes the computation symmetric with respect
: to the two images -- the resulting equation is derived in the
: unpublished note by myself. Briefly, good features are located
: by examining the minimum eigenvalue of each 2 by 2 gradient
: matrix, and features are tracked using a Newton-Raphson method of
: minimizing the difference between the two windows. Multi-resolution
: tracking allows for relatively large displacements between images.
: The affine computation that evaluates the consistency of features
: between non-consecutive frames was implemented by Thorsten
: Thormaehlen several years after the original code and documentation
: were written.