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g2o package

g2o 0~20230806-4.1build1 source package in Ubuntu

Changelog

g2o (0~20230806-4.1build1) noble; urgency=medium

  * No-change rebuild for CVE-2024-3094

 -- Steve Langasek <email address hidden>  Sun, 31 Mar 2024 01:00:52 +0000

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Uploaded by:
Steve Langasek
Uploaded to:
Noble
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Oracular release universe misc
Noble release universe misc

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File Size SHA-256 Checksum
g2o_0~20230806.orig.tar.xz 696.6 KiB 52acdc696d6d8d3e2679cf99c33545c082fe266b544108665f1042d9cc77ae96
g2o_0~20230806-4.1build1.debian.tar.xz 9.3 KiB 8bee951833756621ac8bb99bac032f410a800cbcc9b340617624720298077ff1
g2o_0~20230806-4.1build1.dsc 2.4 KiB 6caee12dddca33ac05d81990babf58dee3d8f133f4df1437e8de443d2e089abc

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Binary packages built by this source

libg2o-dev: C++ framework for optimizing graph-based nonlinear error functions

 A wide range of problems in robotics as well as in computer-vision involve the
 minimization of a non-linear error function that can be represented as a graph.
 Typical instances are simultaneous localization and mapping (SLAM) or bundle
 adjustment (BA). The overall goal in these problems is to find the
 configuration of parameters or state variables that maximally explain a set of
 measurements affected by Gaussian noise. g2o is an open-source C++ framework
 for such nonlinear least squares problems. g2o has been designed to be easily
 extensible to a wide range of problems and a new problem typically can be
 specified in a few lines of code. The current implementation provides solutions
 to several variants of SLAM and BA. g2o offers a performance comparable to
 implementations of state-of-the-art approaches for the specific problems
 (02/2011)
 .
 Development files

libg2o-doc: C++ framework for optimizing graph-based nonlinear error functions

 A wide range of problems in robotics as well as in computer-vision involve the
 minimization of a non-linear error function that can be represented as a graph.
 Typical instances are simultaneous localization and mapping (SLAM) or bundle
 adjustment (BA). The overall goal in these problems is to find the
 configuration of parameters or state variables that maximally explain a set of
 measurements affected by Gaussian noise. g2o is an open-source C++ framework
 for such nonlinear least squares problems. g2o has been designed to be easily
 extensible to a wide range of problems and a new problem typically can be
 specified in a few lines of code. The current implementation provides solutions
 to several variants of SLAM and BA. g2o offers a performance comparable to
 implementations of state-of-the-art approaches for the specific problems
 (02/2011)
 .
 Documentation

libg2o0t64: C++ framework for optimizing graph-based nonlinear error functions

 A wide range of problems in robotics as well as in computer-vision involve the
 minimization of a non-linear error function that can be represented as a graph.
 Typical instances are simultaneous localization and mapping (SLAM) or bundle
 adjustment (BA). The overall goal in these problems is to find the
 configuration of parameters or state variables that maximally explain a set of
 measurements affected by Gaussian noise. g2o is an open-source C++ framework
 for such nonlinear least squares problems. g2o has been designed to be easily
 extensible to a wide range of problems and a new problem typically can be
 specified in a few lines of code. The current implementation provides solutions
 to several variants of SLAM and BA. g2o offers a performance comparable to
 implementations of state-of-the-art approaches for the specific problems
 (02/2011)

libg2o0t64-dbgsym: debug symbols for libg2o0t64