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refs:general
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/external/ceres-solver/docs/
further.tex
4
For a short but informative introduction to the subject we recommend the booklet by Madsel et al.~\cite{madsen2004methods}. For a
general
introduction to non-linear optimization we recommend the text by Nocedal \& Wright~\cite{nocedal2000numerical}. Bj{\"o}rck's book remains the seminal reference on least squares problems~\cite{bjorck1996numerical}. Trefethen \& Bau's book is our favourite text on introductory numerical linear algebra~\cite{trefethen1997numerical}. Triggs et al., provide a thorough coverage of the bundle adjustment problem~\cite{triggs-etal-1999}.
nnlsq.tex
11
is a Non-linear least squares problem~\footnote{Ceres can solve a more
general
version of this problem, but for pedagogical reasons, we will restrict ourselves to this class of problems for now. See section~\ref{chapter:overview} for a full description of the problems that Ceres can solve}. Here $\|\cdot\|$ denotes the Euclidean norm of a vector.
faq.tex
67
No. Ceres was designed from the grounds up to be a non-linear least squares solver. Currently we have no plans of extending it into a
general
purpose non-linear solver.
introduction.tex
6
The key computational cost when solving a non-linear least squares problem is the solution of a linear least squares problem in each iteration. To this end Ceres supports a number of different linear solvers suited for different needs. This includes dense QR factorization (using \eigen) for small scale problems, sparse Cholesky factorization (using \texttt{SuiteSparse}) for
general
sparse problems and specialized Schur complement based solvers for problems that arise in multi-view geometry~\cite{hartley-zisserman-book-2004}.
solving.tex
13
Here, the Jacobian $J(x)$ of $F(x)$ is an $m\times n$ matrix, where $J_{ij}(x) = \partial_j f_i(x)$ and the gradient vector $g(x) = \nabla \frac{1}{2}\|F(x)\|^2 = J(x)^\top F(x)$. Since the efficient global optimization of~\eqref{eq:nonlinsq} for
general
$F(x)$ is an intractable problem, we will have to settle for finding a local minimum.
15
The
general
strategy when solving non-linear optimization problems is to solve a sequence of approximations to the original problem~\cite{nocedal2000numerical}. At each iteration, the approximation is solved to determine a correction $\Delta x$ to the vector $x$. For non-linear least squares, an approximation can be constructed by using the linearization $F(x+\Delta x) \approx F(x) + J(x)\Delta x$, which leads to the following linear least squares problem:
271
where, $B \in \reals^{pc\times pc}$ is a block sparse matrix with $p$ blocks of size $c\times c$ and $C \in \reals^{qs\times qs}$ is a block diagonal matrix with $q$ blocks of size $s\times s$. $E \in \reals^{pc\times qs}$ is a
general
block sparse matrix, with a block of size $c\times s$ for each observation. Let us now block partition $\Delta x = [\Delta y,\Delta z]$ and $g=[v,w]$ to restate~\eqref{eq:normal} as the block structured linear system
305
structure of the matrix, there are, in
general
, two options. The first
323
For
general
sparse problems, if the problem is too large for \texttt{CHOLMOD} or a sparse linear algebra library is not linked into Ceres, another option is the \texttt{CGNR} solver. This solver uses the Conjugate Gradients solver on the {\em normal equations}, but without forming the normal equations explicitly. It exploits the relation
[
all
...]
/external/libogg/doc/libogg/
Makefile.am
6
general
.html index.html ogg_packet.html ogg_packet_clear.html\
/external/valgrind/main/gdbserver_tests/
mssnapshot.stderrB.exp
3
general
valgrind monitor commands:
mchelp.stdoutB.exp
0
general
valgrind monitor commands:
30
general
valgrind monitor commands:
/external/webkit/LayoutTests/dom/xhtml/level3/core/
entitygetinputencoding01.js
79
value returned is null for a internal
general
entity.
/ndk/build/core/
setup-abi.mk
31
# more
general
filtering in the future when introducing other ABIs.
/external/libvorbis/
libvorbis.spec
4
Summary: The Vorbis
General
Audio Compression Codec.
26
general
-purpose compressed audio format for audio and music at fixed
/prebuilts/devtools/tools/lib/
jfreechart-1.0.9.jar
jfreechart-swt-1.0.9.jar
/prebuilts/tools/common/jfreechart/
jfreechart-1.0.9.jar
jfreechart-1.0.9-swt.jar
/prebuilts/tools/common/m2/repository/jfree/jfreechart/1.0.9/
jfreechart-1.0.9.jar
/external/compiler-rt/make/platform/
clang_linux.mk
9
# We don't currently have any
general
purpose way to target architectures other
/prebuilts/tools/common/m2/repository/jfree/jfreechart-swt/1.0.9/
jfreechart-swt-1.0.9.jar
/external/libffi/src/powerpc/
linux64_closure.S
46
# save
general
regs into parm save area
/external/qemu/distrib/sdl-1.2.15/src/video/fbcon/
riva_mmio.h
423
U032
general
;
member in struct:_riva_hw_state
/prebuilts/tools/common/netbeans-visual/
org-netbeans-api-visual.jar
/external/antlr/antlr-3.4/runtime/Ruby/lib/antlr3/
task.rb
15
compilation. This is a
general
utility -- the grammars do
/external/icu4c/test/perf/collationperf/
CollPerf.pl
219
<li>For
general
information on ICU collation see <a href=
/external/libvpx/libvpx/vpx_ports/
x86_abi_support.asm
16
; In
general
, we make the source use 64 bit syntax, then twiddle with it using
/external/webkit/LayoutTests/fast/js/resources/
js-test-pre.js
132
// A
general
-purpose comparator. 'actual' should be a string to be
Completed in 1570 milliseconds
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